Cash transfers: what does the evidence say?

Annexes

Francesca Bastagli, Jessica Hagen-Zanker, Luke Harman, Valentina Barca, Georgina Sturge and Tanja Schmidt, with Luca Pellerano

## Contents

| Annex 1 | Overview of existing cash transfers reviews | 4 | | Annex 2 | Detailed search protocols and study assessment tools | 8 | | Annex 3 | Summary table of searches and reasons for exclusion and flow diagrams | 73 | | Annex 4 | Summary of the evidence base | 89 | | Annex 5 | Evidence: results tables for overall effects disaggregated by gender, and cash transfer design and implementation effects | 95 | Annex 1 Overview of existing cash transfers reviews

This annex provides some additional information on existing cash transfer reviews, which are discussed in Chapter 3. Tables A1.1 and A1.2 below summarise the indicators and methods employed in the systematic reviews covered in Chapter 3. Table A1.3 summarises other review studies that are drawn upon in the discussion on design and implementation features in the same chapter.

Table A1.1 Main indicators reported on in systematic reviews

| Reference | Indicators covered | |----------------------------|-----------------------------------------------------------------------------------| | Baird et al., 2013 | School enrolment; school attendance; school test scores. | | Banks et al., 2016 | Meeting basic needs; reducing poverty; employment; health access; mental health. | | Gaarder et al., 2010 | Indicators reported in meta-analysis: clinic visits; immunisation (partial and full); anthropometric indicators (stunting and wasting). Other outcomes reported on individual programmes include: morbidity (e.g. anaemia, diarrhoea); self-reported health; health behaviour (knowledge and practices); mental health. | | Glassman & Duran, 2013 | Births attended by skilled personnel; tetanus toxoid for mother; giving birth in a hospital; post-partum check-ups/visits after birth; contraceptive use and HIV status; fertility; low birth-weight; peri-natal, neo-natal and maternal mortality. | | Hagen-Zanker et al., 2011 | Poverty indices; expenditure; income. | | IEG, 2014 | Empowerment, voice and agency; domestic violence; fertility; prenatal care, institutional delivery and skilled birth attendance; political participation; access to productive resources; employment; school enrolment; school attendance; child labour; anthropometric indicators. | | Kabeer et al., 2012 | Child and adult labour; migration patterns; household consumption; savings and investment; negative coping mechanisms; informal social protection arrangements; community-wide effects (consumption, loans, transfers, remittances, poverty). | | Lagarde et al., 2009 | Health service utilisation (e.g. health care and antenatal care visits); immunisation coverage; child illness; anthropometric and nutritional indicators. | | Manley et al., 2012 | Anthropometric indicators (child height for age and child height). | | Anthropometric indicators (child height for age and child height), (Review in progress) | Use of health services and health outcomes. | | Saavedra & Garcia, 2012 | School enrolment; school attendance; school dropout rate. | | Yoong et al., 2012 | Anthropometric and nutritional indicators; adult labour supply; household expenditure (health, school, clothing, food); school enrolment; school attendance; investments in business and agriculture; asset ownership; enterprise performance. |

Notes: These are the main outcomes reported. There are some further outcomes reported within individual studies. For studies reporting on interventions other than cash transfers, indicators shown are only those associated with impacts of cash transfers.

### Table A1.2 Study designs and methods included in systematic reviews

| Reference | Study designs accepted for final analysis | Quality assessment of included studies | |--------------------|-----------------------------------------------------------------------------------------------------------|----------------------------------------------------------------------------------------------------------| | Baird et al., 2013 | (i) RCT (ii) Quasi-experimental design with controlled comparison. Required cross-sectional or longitudinal comparison (pre-post control, contemporaneous control, interrupted time series, parallel cohort or RDD). | Risk of bias assessed using tool developed by the International Development Coordinating Group (IDCG). | | Banks et al., 2016 | No restrictions. | Risk of various types of bias evaluated by two authors using modified versions of the assessment tools RATS and STROBE for qualitative and quantitative studies, respectively (Clark, 2003; von Elm et al., 2007). Assessment focused on the risk of potential biases arising from study design, sampling methods, data collection and data analysis interpretation. Studies categorized as: (1) ‘low’ risk of bias, (2) ‘medium’ risk of bias or (3) ‘high’ risk of bias. No strict cut-offs were used in assigning classifications and all papers (including ‘high’ risk) were eventually included. | | Gaarder et al., 2010| (i) Experimental studies (ii) Quasi-experimental design (matching, regression discontinuity design (RDD) and multivariate regression). Excluded studies that did not control for endogeneity of intervention status. | None. | | Glassman & Duran, 2013 | Unclear. Report on studies that report ‘rigorously calculated impacts’. | None. | | Hagen-Zanker et al., 2011 | Solid empirical study with high quality reporting. | Scored studies using an index developed by the authors comprising: reporting on targeting incidence, study design, accounted for income foregone and household economy responses, reporting statistical significance. | | IEG, 2014 | A quantitative impact evaluation that adopted either (i) an experimental or (ii) quasi-experimental design that relied on a credible control group. Graded studies according to strength of internal validity and excluded studies where main methodological assumptions were not discussed and proposed causal relationship weak. | Quality check based on full text review to assess strength of internal validity (i.e. assumptions of evaluation methods verified and treatment of endogeneity assessed). | | Kabeer et al., 2012 | (i) Experimental (ii) Quasi-experimental (RDD, Propensity Score Matching, IV or DID). | None. | | Lagarde et al., 2009 | Examined all studies that met the Effective Practice and Organisation of Care Group (EPOC) inclusion criteria for study design and compared the effects (on predetermined outcomes) of offering CCTs against the absence of CCTs. Then included three types of studies: (i) RCTs or C-RCTs (ii) Pre-post control studies (iii) Interrupted time-series (providing studies defined the point in time of the intervention and there were three or more data points before and after the intervention). | Assessment of risk of bias (based on EPOC) was then carried out to determine quality of evidence, tailored to study design. | | Manley et al., 2012 | Had to be an impact evaluation but no restrictions on study design or methods. | Used two sets of criteria concerning study design and methods based on the Cochrane handbook and scored studies accordingly. | | Saavedra & Garcia, 2012 | Study had to use a “treatment-comparison” research design. Non-randomised studies only eligible if they report relevant pre-treatment characteristics of treatment and comparison groups. Intervention pre-post studies not eligible. | None. | | Yoong et al., 2012 | Had to (i) be an evaluation study of specific programme or programmes and (ii) use an approach aimed at identifying causal effects and their size. Further methodological criteria (adapted from the Maryland Scale of Scientific Methods) were also applied to quantitative studies which had to score 18 or above to be in the final set of papers. Qualitative literature kept for developing conceptual framework and contributing relevant insights. | Studies scored using quality criteria (see cell to left). |

### Table A1.3 Other review papers on impacts of cash transfers

| Reference | Main outcomes covered | Interventions | Number of evaluations | Regional focus? | |-----------|-----------------------|---------------|-----------------------|-----------------| | Adato & Bassett, 2012 | Poverty; education; health; food consumption; nutrition. | UCTs, CCTs and pensions | 40 cash transfer programmes including pensions | No | | Adato & Hoddinott, 2010 | Education; health; nutrition; food consumption; women’s status and gender relations; participation and power. | CCTs | Various evaluations for 4 programmes | Latin America | | Arnold et al., 2011 | Poverty; vulnerability and inequality; nutrition and food security; education; health and population; protecting productive assets; encouraging livelihood diversification; stimulating local markets; access to credit; gdp growth; labour markets; child labour; empowerment and gender equality; humanitarian assistance; state building and social cohesion; climate change adaptation and disaster risk reduction. | UCTs, CCTs non-contributory pensions and PWPs | Not stated | No | | Barrientos & Scott, 2008 | Effects on growth at the micro-level: alleviating credit constraints; addressing insurance failures; improving household resource allocation and dynamics; human development (incl. Health, education and nutrition); labour supply; local economy effects; saving. | Social transfers (PWPs, CCTs, UCTs, social pensions) | At least 31 | No | | Bassett, 2008 | Nutrition. | CCTs | CCTs from 5 countries | Latin America | | Bastagi, 2010 | Poverty; inequality impacts; education; health. | CCTs | 9 CCTs | Latin America | | Bouillon & Tejerina, 2007 | Education (attendance, enrolment, pass rates); nutrition; child labour; health (access and outcomes). | CCTs | 10 covering 10 CCTs | Latin America and the Caribbean | | Fiszbein & Schady, 2009 | Consumption; poverty; employment; education; health. | CCTs | Not stated | No | | Harvey, 2005 | Markets and prices; multiplier effects; household gender relations; | CTs, cash for work and voucher programmes | Various | Humanitarian situations | | IEG, 2011 | **Short-term and intermediate outcomes:** Current income; consumption; poverty; education; child labour; health; nutrition; labour supply; economic activities; protection against idiosyncratic and systemic shocks; **Final outcomes:** Stock of human capital; stock of physical capital; employment, income and consumption trajectories; **Indirect effects:** Remittances and other private transfers; sexual behaviour, fertility and marriage; other intra-household behavioural responses; spillover and general equilibrium effects. | Non-contributory social safety nets | 149 (109 for UCTs or CCTs) | No | | Leroy, Ruel, & Verhofstadt, 2009 | Child nutrition | CCTs | 7 | No | | Mathers & Slater, 2014 | Economic growth and its determinants at the micro level (accumulation of assets and preventing loss of productive capital, increasing innovation and risk-taking, investing in human capital, improved employment opportunities) and meso level (multiplier effects from increased consumption and production, accumulation of productive community assets and labour market impacts) | Non-contributory transfers | Not stated | No | | Ranganathan & Lagarde, 2012 | Uptake of health services; immunisation coverage; nutrition; health; health behaviour. | CCTs (with a condition on health) | 19 (of 13 CCTs) | No | | Rawlings & Rubio, 2003 | Education; child labour; health; consumption. | CCTs | Various evaluations (3 CCTs) | Latin America | | Reimers, DeShano da Silva, & Trevino, 2006 | Education | Non-contributory transfers (scholarships/fee waivers, CCTs, food transfers) | Various evaluations for 9 programmes (not all traditional CCTs) | No | | Reference | Main outcomes covered | Interventions | Number of evaluations | Regional focus? | |-----------|-----------------------|---------------|-----------------------|-----------------| | Tirivayi, Knowles, & Davis, 2013 | Direct impacts on farm production (agricultural assets, inputs, labour allocation, agricultural output); indirect impacts on farm production (human capital accumulation, off-farm investments, reduction of adverse risk-coping strategies); local economy effects. | Non-contributory schemes (CTs, PWPs, school feeding, food aid, social pensions and education fee waivers) | ~160 | Sub-Saharan Africa, Latin America and Asia | | Yablonski & O’Donnell, 2009 | Child mortality and determinants (e.g. illness, nutrition, access to healthcare, access to food, care for women and children, household environment and hygiene); economic (e.g. Labour market, investments local multiplier effects). | CTs | Unclear | No | | Barrientos, Niño-Zarazúa, & Maitrot, 2010 | Database of key features of numerous social assistance interventions with links to evaluations. | Social assistance (including CTs and social pensions) | Includes summary of 42 ‘pure income transfers’ with links to related evaluations | No | | Devereux, Marshall, MacAskill, & Pelham, 2005 | Qualitative review of programme design, delivery issues and potential benefits of scaling-up. | UCTs (including social pensions, disability grants and orphan support schemes) | Reviews range of schemes in 15 countries and 4 in-depth | East and Southern Africa | | Garcia & Moore, 2012 | Mainly a synthesis describing design and implementation features | UCTs and CCTs | 123 cash transfer programmes | Sub-Saharan Africa | | Monchuk, 2014 | Review focused on objectives, features, systems, general performance, and financing. Very limited on reviewing impacts. | Safety nets (cash transfers, public works and school feeding) | Mainly based on 22 safety net and social protection World Bank assessments of the 22 countries covered | Sub-Saharan Africa | Annex 2 Detailed search protocols and study assessment tools

This annex provides additional information on the methods used in the review. Part 1 lists the detailed search protocols used in the literature searches.

Part 2 reports the tools used in the second stage screening process to assess the studies retrieved against agreed methodological criteria. For quantitative impact analysis studies, the final stage of screening included assessing studies against: selection bias and confounding factors, attrition bias, statistical significance (biases leading to Type I or Type II errors) and any other bias. To pass, these studies had to demonstrate ‘low’ risk of bias or ‘low’ and ‘unclear’ risk of bias. Qualitative studies retrieved under searches for evidence of links between policy design and implementation features and outcomes, were assessed against: clarity and transparency, credibility of findings, acknowledgement of potential internal bias and limitations, and external validity. Studies passed if they were considered to have either ‘no concerns’, or ‘no concerns’ and ‘some concerns’ within the same study. Part 1. Detailed search protocols

Separate protocols were developed to carry out searches for the six outcomes and six key cash transfer design and implementation features put forward in the conceptual framework. A total of 12 separate searches were carried out. The remainder of Part 1 lists the specific search protocols employed in the literature searches for each outcome and cash design and implementation feature. Sub-question 1a: What is the effect of cash transfers on monetary poverty and inequality?

1. The review research questions

The systematic literature reviews should assess the state of knowledge on the following question: *What is known about the effect of cash transfers on monetary poverty and inequality?*

2. Methodology

The systematic literature reviews should combine three tracks. These tracks are briefly explained here and further instructions are given below.

1. **Bibliographic database search:** Searching a previously agreed upon list of academic databases, using consistent search strings (see below) that have been tested beforehand and applying inclusion/exclusion criteria.

2. **Snowball technique:** Contacting approximately three key experts in the field and asking them for recommendations for important studies on the research question. This also includes looking at the experts’ websites and publication lists and including relevant studies. Finally, we will be looking for further relevant studies in the bibliographies of the experts’ studies and recommended studies.

3. **Websites searches:** Searching previously agreed on websites (see below) for relevant studies using similar search terms as for the bibliographic databases. This also includes a google search for other grey literature.

Studies will be screened and assessed using the EPPI Reviewer software. After an initial broad screening process that considers overall study design, as well as other broader inclusion/exclusion criteria, a second round of screening will be conducted and studies will be assessed against a range of criteria to investigate the risk of bias and reliability of findings. Specifically, studies will be assessed against the issues of selection bias, attrition bias or bias associated with interpretation of statistical significance (Type I or Type II errors). Studies that have a high risk of bias or score low on rigour will be not be included in the final analysis.

The relevant studies that make it through both stages of screening will be summarised in an annotated bibliography. The annotated bibliography lists the relevant studies in table format (see below) and briefly summarises each study in terms of relevant information on methodology, intervention and findings. More specifically, the relevant studies will also be summarised and classified in a table summarising the following information: i) publication details, (ii) description of the intervention and context, (iii) methods, data and sampling, (iv) population, v) findings of relevance to the research question including findings of statistically significant and non-significant impacts and disaggregation (e.g. by gender, age and other characteristics), and vi) contextual factors of importance.

A narrative synthesis approach will be applied to synthesise the findings. 3. Bibliographic database search

The research question

The research question is ‘What is known about the effect of cash transfers on monetary poverty and inequality?’ Here we want to know the effect on household income, expenditure, monetary poverty and inequality.

In order to understand it better, the research question can be decomposed into population, intervention and outcome:

| Population | Intervention | Outcome | |------------|--------------|---------| | People living in low or middle income countries and who either receive the intervention or are the comparison group | Conditional or unconditional cash transfers | Monetary poverty and inequality |

| Cash transfer | Income | | Social transfer | Earning\* | | Financial transfer | Cash | | Monetary transfer | Expenditure | | Child grant/ disability grant/ old-age grant/ social grant | Spending | | Social assistance | Consumption | | Social pension | Purchas\* | | Non-contributory pension | Foster Greer Thorbecke | | Old age pension | FGT | | Child benefit/ disability benefit/ old-age benefit | Poverty headcount | | Basic income/ minimum income | Poverty gap | | UCT/ CCT | Poverty depth | | Income support | Poverty severity | | | Gini | | | Benefit incidence | | | Inequality | | | Distribution |

The population has been restricted to people living in low and middle income countries. This includes both beneficiary and control households. The aim of the research question is to analyse the impact of cash transfers on monetary poverty and inequality. The outcome for this sub-question is income, expenditure, monetary poverty and inequality. The table above also includes all synonyms that will be used in the searches.

Search strings

The search string will be composed of intervention (part 1), outcome (part 2) and country filter (example below given for SCOPUS filter). In order to capture all possible cash transfers, search strings should include all synonyms listed above. In terms of outcome, we will use synonyms of income, expenditure, monetary poverty and inequality in the search strings. The following search strings will be used (they have been tested in the pilot phase):

1. TITLE-ABS-KEY ( “Cash transfer\*” OR “social transfer\*” OR “financial transfer\*” OR “monetary transfer\*” OR “child grant\*” OR “disability grant\*” OR “old age grant\*” OR “social grant\*” OR “basic grant\*” OR “minimum income grant\*” OR “social assistance” OR welfare OR “social pension\*” OR “non-contributory pension\*” OR “old age pension\*” OR “child benefit\*” OR “disability benefit\*” OR “old age benefit\*” OR “cct” OR “uct” OR “income support” )

2. TITLE-ABS-KEY ( income\* OR earning\* OR cash OR expend\* OR spending OR consumption OR purchas\* OR “Foster Greer Thorbecke” OR fgt OR “poverty headcount” OR “poverty gap” OR “poverty depth” OR “depth of poverty” OR “poverty severity” OR “severity of poverty” OR gini OR inequalit\* OR inequit\* OR distribution )

- note this should search title/abstract/keyword or subject fields

3. TITLE-ABS-KEY (afghanistan OR albania OR algeria OR angola OR argentina OR armenia OR armenian OR aruba OR azerbaijan OR bangladesh OR benin OR belarus OR belorussian OR belorussia OR belize OR bhutan OR bolivia OR bosnia OR herzegovina OR hercegovina OR botswana OR brasil OR brazil OR bulgaria OR “Burkina Faso” OR “Burkina Fasso” OR “Upper Volta” OR burundi OR urundi OR cambodia OR “Khmer Republic” OR kampuchea OR cameroon OR cameroons OR cameron OR camorons OR “Cape Verde” OR “Central African Republic” OR chad OR china OR colombia OR comoros OR “Comoro Islands” OR comores OR mayotte OR congo OR zaire OR “Costa Rica” OR “Cote d’Ivoire” OR “Ivory Coast” OR cuba OR djibouti OR “French Somaliland” OR dominica OR “Dominican Republic” OR “East Timor” OR “East Timur” OR “Timor Leste” OR ecuador OR egypt OR “United Arab Republic” OR “El Salvador” OR eritrea OR ethiopia OR fiji OR gabon OR “Gabonese Republic” OR gambia OR gaza OR “Georgia Republic” OR “Georgian Republic” OR ghana OR grenada OR guatemala OR guinea OR guiana OR guyana OR haiti OR hungary OR honduras OR india OR maldives OR indonesia OR iran OR iraq OR jamaica OR jordan OR kazakhstan OR kazakh OR keny OR kiribati OR korea OR kosovo OR kyrgyzstan OR kirghizia OR “Kyrgyz Republic” OR kirghiz OR kirgizstan OR “Lao PDR” OR laos OR lebanon OR lesotho OR basutoland OR liberia OR libya OR macedonia OR madagascar OR “Malagasy Republic” OR malaysia OR malaya OR malay OR sabah OR sarawak OR malawi OR mali OR “Marshall Islands” OR mauritania OR mauritius OR “Agalega Islands” OR mexico OR micronesia OR “Middle East” OR moldova OR moldavia OR moldovan OR mongolia OR montenegro OR morocco OR ifni OR mozambique OR myanmar OR myanmar OR burma OR namibia OR nepal OR “Netherlands Antilles” OR “New Caledonia” OR nicaragua OR niger OR nigeria OR pakistan OR palau OR palestine OR panama OR paraguay OR peru OR philippines OR philippines OR philippines OR philippines OR “Puerto Rico” OR romania OR rumania OR roumania OR rwanda OR ruanda OR “Saint Lucia” OR “St Lucia” OR “Saint Vincent” OR “St Vincent” OR grenadines OR samoan OR “Samoan Islands” OR “Navigator Island” OR “Navigator Islands” OR “Sao Tome” OR senegal OR serbia OR montenegro OR seychelles OR “Sierra Leone” OR “Sri Lanka” OR “Solomon Islands” OR somalia OR “South Africa” OR sudan OR suriname OR surinam OR swaziland OR syria OR tajikistan OR tajikistan OR tadjikistan OR tadjik OR tanzania OR thailand OR togo OR togoles republic OR tonga OR tunisia OR turkey OR turkmenistan OR turkmen OR uganda OR ukraine OR uzbekistan OR uzbek OR vanuatu OR “New Hebrides” OR venezuela OR vietnam OR “Viet Nam” OR “West Bank” OR yemen OR yugoslavia OR zambia OR zimbabwe ) OR TITLE-ABS-KEY (“Developing Countries” OR africa OR asia OR caribbean OR “West Indies” OR “South America” OR “Latin America” OR “Central America” OR developing OR “less\* developed” OR “under developed” OR underdeveloped OR “middle income” OR “low\* income” OR underserved OR “under served” OR deprived) OR TITLE-ABS-KEY (poor\* W/1 countr\* OR nation\* OR population\* OR world ) OR TITLE-ABS-KEY (developing OR “less\* developed” OR “under developed” OR underdeveloped OR “middle income” OR “low\* income” ) W/1 econom\* ) OR TITLE-ABS-KEY (low\* W/1 gdp OR gnp OR “gross domestic” OR “gross national” ) OR TITLE-ABS-KEY (low W/3 middle W/3 countr\* ) OR TITLE-ABS-KEY ( lmic OR lmc OR “third world” OR “lami countr\*” OR “transitional countr\*” )

4. Search strings to run in Scopus: #1 AND #2 AND #3 (limited to 2000 onwards) Inclusion criteria

Stage 1 Screening:

Inclusion criteria help in deciding whether a study that has been found is relevant. The following inclusion criteria will be applied during the first stage of the screening process (all criteria need to be satisfied for the study to be included). They will be applied to titles, then abstracts, then full text. All studies that are included on the basis of the first stage screening process, will be included in the Stage 2 screening process.

1. **Date**: From 2000

2. **Language**: The review is restricted to English studies

3. **Population**: People that have received a cash transfer, or control households

4. **Geographical locations**: Low and middle income countries

5. **Interventions**: Conditional or unconditional cash transfers. The programmes should be non-contributory, publicly mandated or NGO-provided (so not private transfers, like remittances, or religious donations).

6. **Study design**: The study should be a solid empirical study (i.e. based on data and or fieldwork). Only studies that use either an experimental design or a quasi-experimental design that relies on a credible control group should be included. This includes those that demonstrate one of the following: (a) an experimental design (i.e. RCT or cluster-RCT) (b) a quasi-experimental design, including: i. regression discontinuity design ii. matching technique (e.g. propensity score matching) iii. difference-in-difference iv. interrupted time series v. other form of multivariate regression, including Instrumental Variable Technique, including Instrumental Variable Technique

   [Exclude studies that are theoretical; literature reviews; not descriptive or don’t have an experimental/ quasi-experimental design]

7. **Outcome**: income, expenditure, monetary poverty and inequality

Stage 2 Screening:

In the second round of screening, studies will be will be assessed against a range of criteria to investigate the risk of bias and reliability of findings. Specifically, studies will be assessed against the issues of selection bias, attrition bias or bias associated with interpretation of statistical significance (Type I or Type II errors). Studies that have a high risk of bias or score low on rigour will be not be included in the final analysis.

List of databases used

- SCOPUS (Elsevier). This database includes 5,682 journals, conference proceedings, trade publications and book series in the Social Sciences category.
- Econlit
- IDEAS-Repec

4. Snowball technique

The following three people should be contacted and asked for the five most relevant studies on the research question. We will also look at their websites for relevant publications.

1. John Hoddinot, IFPRI
2. Armando Barrientos, Manchester
3. Ruslan Yemtsov, World Bank

Studies shared by experts will be assessed against Stage 1 and Stage 2 screening criteria. We will also check the reference lists of the studies obtained for any further studies that fit the inclusion criteria.

5. Websites searches

The following websites/search engines should be consulted, if possible using the same search strings as for the academic databases. Any studies found on these websites will be assessed against the same Stage 1 and Stage 2 screening criteria.

- Google (the first five pages)
- World Bank
- R4D DFID
- International Policy Centre for Inclusive Growth (IPC-IG)
- International Food Policy Research Institute (IFPRI)
- Poverty Action Research Lab
- FAO From Protection to Production website
- Transfer Project (UNC Chapel Hill)
- GSDRC
- OPM website
- 3iE website
- ECLAC/CEPAL
- IADB website
- ADB website
- IDS website
- BLDS website
- Social Science Research Network

6. Classification of studies

Studies that have passed both screening stages will be classified and described in an annotated bibliography. The classification tables will include the following information:

- authors and year of study
- geographical coverage
- detailed description of intervention and context
- population
- methods, sampling and data
- a summary of the main outcomes of the study Sub-question 1b: What is the effect of cash transfers on education?

1. The review research questions

The systematic literature reviews should assess the state of knowledge on the following question: *What is known about the effect of cash transfers on education?*

2. Methodology

The systematic literature reviews should combine three tracks. These tracks are briefly explained here and further instructions are given below.

1. **Bibliographic database search:** Searching a previously agreed upon list of academic databases, using consistent search strings (see below) that have been tested beforehand and applying inclusion/exclusion criteria.

2. **Snowball technique:** Contacting approximately three key experts in the field and asking them for recommendations for important studies on the research question. This also includes looking at the experts’ websites and publication lists and including relevant studies. Finally, we will be looking for further relevant studies in the bibliographies of the experts’ studies and recommended studies.

3. **Websites searches:** Searching previously agreed on websites (see below) for relevant studies using similar search terms as for the bibliographic databases. This also includes a google search for other grey literature.

Studies will be screened and assessed using the EPPI Reviewer software. After an initial broad screening process that considers overall study design, as well as other broader inclusion/exclusion criteria, a second round of screening will be conducted and studies will be assessed against a range of criteria to investigate the risk of bias and reliability of findings. Specifically, studies will be assessed against the issues of selection bias, attrition bias or bias associated with interpretation of statistical significance (Type I or Type II errors). Studies that have a high risk of bias or score low on rigour will be not be included in the final analysis.

The relevant studies that make it through both stages of screening will be summarised in an annotated bibliography. The annotated bibliography lists the relevant studies in table format (see below) and briefly summarises each study in terms of relevant information on methodology, intervention and findings. More specifically, the relevant studies will also be summarised and classified in a table summarising the following information: i) publication details, (ii) description of the intervention and context, (iii) methods, data and sampling, (iv) population, (v) findings of relevance to the research question including findings of statistically significant and non-significant impacts and disaggregation (e.g. by gender, age and other characteristics), and (vi) contextual factors of importance.

A narrative synthesis approach will be applied to synthesise the findings. 3. Bibliographic database search

The research question

The research question is ‘What is known about the effect of cash transfers on education?’ Here we want to know the effect on school enrolment, school attendance and school achievement.

In order to understand it better, the research question can be decomposed into population, intervention and outcome:

| Population | Intervention | Outcome | |------------|--------------|---------| | People living in low or middle income countries and who either receive the intervention or are the comparison group | Conditional or unconditional cash transfers | School enrolment, school attendance and school achievement |

| Cash transfer | Social transfer | Financial transfer | Monetary transfer | Child grant/ disability grant/ old-age grant/ social grant | Social assistance | Social pension | Non-contributory pension | Old age pension | Child benefit/ disability benefit/ old-age benefit | Basic income/ minimum income | UCT/ CCT | Income support | |---------------|-----------------|-------------------|------------------|----------------------------------------------------------|-----------------|-----------------|------------------------|----------------|-----------------------------------------------|-----------------------------|----------|---------------| | Education | School | Enrol\* | Registration | Admission | Attend\* | Participation | Retention | Drop-out | Completion | Achievement | Learning | Repetition / repeat\* | | | | | | | | | | | | Graduation / graduate\* | | |

The population has been restricted to people living in low and middle income countries. This includes both beneficiary and control households. The aim of the research question is to analyse the impact of cash transfers on any level of education. The outcome for this sub-question is school enrolment, school attendance and school achievement. The table above also includes all synonyms that will be used in the searches.

Search strings

The search string will be composed of intervention (part 1), outcome (part 2) and country filter (example below given for SCOPUS filter). In order to capture all possible cash transfers, search strings should include all synonyms listed above. In terms of outcome, we will use school enrolment, school attendance and school achievement and synonyms in the search strings. The following search strings and will be used (they have been tested in the pilot phase):

1. TITLE-ABS-KEY ( “Cash transfer\*” OR “social transfer\*” OR “financial transfer\*” OR “monetary transfer\*” OR “child grant\*” OR “disability grant\*” OR “old age grant\*” OR “social grant\*” OR “basic grant\*” OR “minimum income grant\*” OR “social assistance” OR “welfare” OR “social pension\*” OR “non-contributory pension\*” OR “old age pension\*” OR “child benefit\*” OR “disability benefit\*” OR “old age benefit\*” OR “cct” OR “uct” OR “income support”)

2. TITLE-ABS-KEY ((school\* OR education\*) AND ( enrol\* OR regist\* OR admission\* OR attend\* OR participat\* OR retention OR retain\* OR drop-out\* OR complet\* OR attain\* OR learn\* OR progress\* OR cognitive OR repeat\* OR repetition OR graduat\* OR achiev\* ) )

3. TITLE-ABS-KEY (afghanistan OR albania OR algeria OR angola OR argentina OR armenia OR armenian OR aruba OR azerbaijan OR bangladesh OR benin OR belarus OR belorussian OR belorussia OR belize OR bhutan OR bolivia OR bosnia OR herzegovina OR hercegovina OR botswana OR brasil OR brazil OR bulgaria OR “Burkina Faso” OR “Burkina Fasso” OR “Upper Volta” OR burundi OR urundi OR cambodia OR “Khmer Republic” OR kampuchea OR cameroon OR cameroons OR cameron OR camorons OR “Cape Verde” OR “Central African Republic” OR chad OR china OR colombia OR comoros OR “Comoro Islands” OR comores OR mayotte OR congo OR zaire OR “Costa Rica” OR “Cote d’Ivoire” OR “Ivory Coast” OR cuba OR djibouti OR “French Somaliland” OR dominica OR “Dominican Republic” OR “East Timor” OR “East Timur” OR “Timor Leste” OR ecuador OR egypt OR “United Arab Republic” OR “El Salvador” OR eritrea OR ethiopia OR fiji OR gabon OR “Gabonese Republic” OR gambia OR gaza OR “Georgia Republic” OR “Georgian Republic” OR ghana OR grenada OR guatemala OR guinea OR guiana OR guyana OR haiti OR hungary OR honduras OR india OR maldives OR indonesia OR iran OR iraq OR jamaica OR jordan OR kazakhstan OR kazakh OR keny OR kiribati OR korea OR kosovo OR kyrgyzstan OR kirghizia OR “Kyrgyz Republic” OR kirghiz OR kirgizstan OR “Lao PDR” OR laos OR lebanon OR lesotho OR basutoland OR libera OR libya OR macedonia OR madagascar OR “Malagasy Republic” OR malaysia OR malaya OR malay OR sabah OR sarawak OR malawi OR mali OR “Marshall Islands” OR mauritania OR mauritius OR “Agalega Islands” OR mexico OR micronesia OR “Middle East” OR moldova OR moldavia OR moldovan OR mongolia OR montenegro OR morocco OR ifni OR mozambique OR myanmar OR myamna OR burma OR namibia OR nepal OR “Netherlands Antilles” OR “New Caledonia” OR nicaragua OR niger OR nigeria OR pakistan OR palau OR palestine OR panama OR paraguay OR peru OR philippines OR philippines OR philippines OR philippines OR “Puerto Ric\*” OR romania OR rumania OR roumania OR rwanda OR ruanda OR “Saint Lucia” OR “St Lucia” OR “Saint Vincent” OR “St Vincent” OR grenadines OR samoan OR “Samoan Islands” OR “Navigator Island” OR “Navigator Islands” OR “Sao Tome” OR senegal OR serbia OR montenegro OR seychelles OR “Sierra Leone” OR “Sri Lanka” OR “Solomon Islands” OR somalia OR “South Africa” OR sudan OR suriname OR surinam OR swaziland OR syria OR tajikistan OR tadjikistan OR tadjik OR tanzania OR thailand OR togo OR togoles republic OR tonga OR tunisia OR turkey OR turkmenistan OR turkmen OR uganda OR ukraine OR uzbekistan OR uzbek OR vanuatu OR “New Hebrides” OR venezuela OR vietnam OR “Viet Nam” OR “West Bank” OR yemen OR yugoslavia OR zambia OR zimbabwe ) OR TITLE-ABS-KEY (“Developing Countries” OR africa OR asia OR caribbean OR “West Indies” OR “South America” OR “Latin America” OR “Central America” OR developing OR “less\* developed” OR “under developed” OR underdeveloped OR “middle income” OR “low\* income” OR underserved OR “under served” OR deprived) OR TITLE-ABS-KEY (poor\* W/1 countr\* OR nation\* OR population\* OR world ) OR TITLE-ABS-KEY (developing OR “less\* developed” OR “under developed” OR underdeveloped OR “middle income” OR “low\* income” ) W/1 econom\* ) OR TITLE-ABS-KEY (low\* W/1 gdp OR gnp OR “gross domestic” OR “gross national” ) OR TITLE-ABS-KEY (low W/3 middle W/3 countr\* ) OR TITLE-ABS-KEY ( lmic OR lmic\* OR “third world” OR “lami countr\*” OR “transitional countr\*” )

4. Search strings to run in Scopus: #1 AND #2 AND #3 (limited to 2000 onwards) Inclusion criteria

Stage 1 Screening:

Inclusion criteria help in deciding whether a study that has been found is relevant. The following inclusion criteria will be applied during the first stage of the screening process (all criteria need to be satisfied for the study to be included). They will be applied to titles, then abstracts, then full text. All studies that are included on the basis of the first stage screening process, will be included in the Stage 2 screening process.

1. **Date**: From 2000
2. **Language**: The review is restricted to English studies
3. **Population**: People that have received a cash transfer, or control households
4. **Geographical locations**: Low and middle income countries
5. **Interventions**: Conditional or unconditional cash transfers. The programmes should be non-contributory, publicly mandated or NGO-provided (so not private transfers, like remittances, or religious donations).
6. **Study design**: The study should be a solid empirical study (i.e. based on data and or fieldwork). Only studies that use either an experimental design or a quasi-experimental design that relies on a credible control group should be included. This includes those that demonstrate one of the following: (a) an experimental design (i.e. RCT or cluster-RCT) (b) a quasi-experimental design, including: i. regression discontinuity design ii. matching technique (e.g. propensity score matching) iii. difference-in-difference iv. interrupted time series v. other form of multivariate regression, including Instrumental Variable Technique. [Exclude studies that are theoretical; literature reviews; not descriptive or don’t have an experimental/ quasi-experimental design]
7. **Outcome**: School enrolment, school attendance and school achievement

Stage 2 Screening:

In the second round of screening, studies will be will be assessed against a range of criteria to investigate the risk of bias and reliability of findings. Specifically, studies will be assessed against the issues of selection bias, attrition bias or bias associated with interpretation of statistical significance (Type I or Type II errors). Studies that have a high risk of bias or score low on rigour will be not be included in the final analysis.

List of databases used

- SCOPUS (Elsevier). This database includes 5,682 journals, conference proceedings, trade publications and book series in the Social Sciences category.
- IDEAS-REPEC

4. Snowball technique

The following three people should be contacted and asked for the five most relevant studies on the research question. We will also look at their websites for relevant publications.

1. Sarah Baird, George Washington University
2. Jaime Saavedra-Chanduvi, World Bank
3. Fernando M. Reimers, Harvard University

Studies shared by experts will be assessed against Stage 1 and Stage 2 screening criteria. We will also check the reference lists of the studies obtained for any further studies that fit the inclusion criteria.

5. Websites searches

The following websites/search engines should be consulted, if possible using the same search strings as for the academic databases. Any studies found on these websites will be assessed against the same Stage 1 and Stage 2 screening criteria.

- Google (the first five pages)
- World Bank
- R4D DFID
- International Policy Centre for Inclusive Growth (IPC-IG)
- International Food Policy Research Institute (IFPRI)
- Poverty Action Research Lab
- FAO From Protection to Production website
- Transfer Project (UNC Chapel Hill)
- GSDRC
- OPM website
- 3iE website
- ECLAC/CEPAL
- IADB website
- ADB website
- UNICEF website
- IDS website
- BLDS website
- Social Science Research Network

6. Classification of studies

Studies that have passed both screening stages will be classified and described in an annotated bibliography. The classification tables will include the following information:

- authors and year of study
- geographical coverage
- detailed description of intervention and context
- population
- methods, sampling and data
- a summary of the main outcomes of the study Sub-question 1c: What is the effect of cash transfers on health?

1. The review research questions

The systematic literature reviews should assess the state of knowledge on the following question: *What is known about the effect of cash transfers on health?*

2. Methodology

The systematic literature reviews should combine three tracks. These tracks are briefly explained here and further instructions are given below.

1. **Bibliographic database search:** Searching a previously agreed upon list of academic databases, using consistent search strings (see below) that have been tested beforehand and applying inclusion/exclusion criteria.

2. **Snowball technique:** Contacting approximately four key experts in the field and asking them for recommendations for important studies on the research question. This also includes looking at the experts’ websites and publication lists and including relevant studies. Finally, we will be looking for further relevant studies in the bibliographies of the experts’ studies and recommended studies.

3. **Websites searches:** Searching previously agreed on websites (see below) for relevant studies using similar search terms as for the bibliographic databases. This also includes a google search for other grey literature.

Studies will be screened and assessed using the EPPI Reviewer software. After an initial broad screening process that considers overall study design, as well as other broader inclusion/exclusion criteria, a second round of screening will be conducted and studies will be assessed against a range of criteria to investigate the risk of bias and reliability of findings. Specifically, studies will be assessed against the issues of selection bias, attrition bias or bias associated with interpretation of statistical significance (Type I or Type II errors). Studies that have a high risk of bias or score low on rigour will be not be included in the final analysis.

The relevant studies that make it through both stages of screening will be summarised in an annotated bibliography. The annotated bibliography lists the relevant studies in table format (see below) and briefly summarises each study in terms of relevant information on methodology, intervention and findings. More specifically, the relevant studies will also be summarised and classified in a table summarising the following information: i) publication details, (ii) description of the intervention and context, (iii) methods, data and sampling, (iv) population, v) findings of relevance to the research question including findings of statistically significant and non-significant impacts and disaggregation (e.g. by gender, age and other characteristics), and vi) contextual factors of importance.

A narrative synthesis approach will be applied to synthesise the findings. 3. Bibliographic database search

The research question

The research question is ‘What is known about effect of cash transfers on health?’ Here we want to know the effect of cash transfers on health outcomes, health access, health utilisation, and nutrition.

In order to understand it better, the research question can be decomposed into population, intervention and outcome:

| Population | Intervention | Outcome | |------------|--------------|---------| | People living in low or middle income countries and who either receive the intervention or are the comparison group | Conditional or unconditional cash transfers | Health outcomes, health access, health utilisation, and nutrition |

Cash transfer Social transfer Financial transfer Monetary transfer Child grant/ disability grant/ old-age grant/ social grant Social assistance Social pension Non-contributory pension Old age pension Child benefit/ disability benefit/ old-age benefit Basic income/ minimum income UCT/ CCT Income support

Food diversity Dietary diversity Food variety Vitamins Diet Food security/ food insecurity Food intake Nutrition\* Calor\* Nutrition\* supplement + Obesity Health util*ation Health use Number of visits Health access Health service Health centre Hospital Clinic Health care provider Health fee Health payment Prenatal / antenatal/ postnatal care and access Institutional deliver Vaccinations/Immuni* Screening Health Healthiness Sickness Illness Disease Stunting Wasting Weight Birth weight Immun\*ation Child height and weight for age Body mass index WAZ/ WHZ/ HAZ/ BMIZ Maternal mortality Newborn mortality Morbidity HIV prevention HIV/ AIDS incidence

The population has been restricted to people living in low and middle income countries. This includes both beneficiary and control households. The aim of the research question is to analyse the impact of cash transfers on health. The outcome for this sub-question is health outcomes, health access, health utilisation, and nutrition. The table above also includes all synonyms that will be used in the searches. Search strings

The search string will be composed of intervention (part 1), outcome (part 2) and country filter (example below given for SCOPUS filter). In order to capture all possible cash transfers, search strings should include all synonyms listed above. In terms of outcome, we will use health outcomes, health access, health utilisation, and nutrition and synonyms in the search strings. The following search strings and will be used (they have been tested in the pilot phase):

1. TITLE-ABS-KEY ( “Cash transfer\*” OR “social transfer\*” OR “financial transfer\*” OR “monetary transfer\*” OR “child grant\*” OR “disability grant\*” OR “old age grant\*” OR “social grant\*” OR “basic grant\*” OR “minimum income grant\*” OR “social assistance” OR welfare OR “social pension\*” OR “non-contributory pension\*” OR “old age pension\*” OR “child benefit\*” OR “disability benefit\*” OR “old age benefit\*” OR cct OR uct OR “income support” )

2. TITLE-ABS-KEY (“food diversity” OR “dietary diversity” OR “food variety” OR vitamin\* OR diet OR “food security” OR “food insecurity” OR “food intake” OR nutrition\* OR calor\* OR obesity OR “health service\*” OR “health centre\*” OR “health center\*” OR “health care provider” OR “institutional delivery” OR “health access” OR “health utilisation” OR “health utilization” OR “health use” OR hospital\* OR clinic\* OR “health fee\*” OR “health payment\*” OR “prenatal care” OR “post-natal care” OR “ante-natal care” OR vaccinat\* OR immuniz\* OR immunis\* OR health\* OR sickness OR illness OR disease OR stunting OR wasting OR “child weight” OR “child height” OR “height for age” OR “weight for age” OR “body mass index” OR BMI OR “maternal mortality” OR “infant mortality” OR morbidity OR HIV W/4 (prevent\* OR incidence) OR AIDS W/4 incidence OR WAZ OR WHZ OR HAZ OR BMIZ OR screen\* )

3. TITLE-ABS-KEY ( afghanistan OR albania OR algeria OR angola OR argentina OR armenia OR armenian OR aruba OR azerbaijan OR bangladesh OR benin OR byelarus OR byelorussian OR belarus OR belorussian OR belorussia OR belize OR bhutan OR bolivia OR bosnia OR herzegovina OR hercegovina OR botswana OR brasil OR brazil OR bulgaria OR “Burkina Faso” OR “Burkina Fasso” OR “Upper Volta” OR burundi OR urundi OR cambodia OR “Khem Republic” OR kampuchea OR cameroon OR cameroons OR cameran OR “Cape Verde” OR “Central African Republic” OR Chad OR china OR colombia OR comoros OR “Comoro Islands” OR comores OR mayotte OR congo OR zaire OR “Costa Rica” OR “Cote d’Ivoire” OR “Ivory Coast” OR cuba OR djibouti OR “French Somaliland” OR dominica OR “Dominican Republic” OR “East Timor” OR “East Timur” OR “Timor Leste” OR ecuador OR egypt OR “United Arab Republic” OR “El Salvador” OR eritrea OR ethiopia OR fiji OR gabon OR “Gabonese Republic” OR gambia OR gaza OR “Georgia Republic” OR “Georgian Republic” OR ghana OR grenada OR guatemala OR guinea OR guiana OR guyana OR haiti OR hungary OR honduras OR india OR maldives OR indonesia OR iran OR iraq OR jamaica OR jordan OR kazakhstan OR kazakh OR kenya OR kiribati OR korea OR kosovo OR kyrgyzstan OR kirghizia OR “Kyrgyz Republic” OR kirghiz OR kirgistan OR “Lao PDR” OR laos OR lebanon OR lesotho OR basutoland OR liberia OR libya OR macedonia OR madagascar OR “Malagasy Republic” OR malaysia OR malaya OR malay OR sabah OR sarawak OR malawi OR mali OR “Marshall Islands” OR mauritania OR mauritius OR “Agalega Islands” OR mexico OR micronesia OR “Middle East” OR moldova OR moldovia OR moldovian OR mongolia OR montenegro OR morocco OR ifni OR mozambique OR myanmar OR myanma OR burma OR namibia OR nepal OR “Netherlands Antilles” OR “New Caledonia” OR nicaragua OR niger OR nigeria OR pakistan OR palau OR palestine OR panama OR paraguay OR peru OR philippines OR philipines OR philippines OR “Puerto Ric\*” OR romania OR rumania OR roumania OR rwanda OR ruanda OR “Saint Lucia” OR “St Lucia” OR “Saint Vincent” OR “St Vincent” OR grenadines OR samoa OR “Samoa Islands” OR “Navigator Island” OR “Navigator Islands” OR “Sao Tome” OR senegal OR serbia OR montenegro OR seychelles OR “Sierra Leone” OR “Sri Lanka” OR “Solomon Islands” OR somalia OR “South Africa” OR sudan OR suriname OR surinam OR swaziland OR syria OR tajikistan OR tadzhikistan OR tadzikistan OR tadzhik OR tanzania OR thailand OR togo OR togoele republic OR tonga OR tunisia OR turkey OR turkmenistan OR turkmen OR uganda OR ukraine OR uzbek OR vanuatu OR “New Hebrides” OR venezuela OR vietnam OR “Viet Nam” OR “West Bank” OR yemen OR yugoslavia OR zambia OR zimbabwe ) OR TITLE-ABS-KEY (“Developing Countries” OR africa OR asia OR caribbean OR “West Indies” OR “South America” OR “Latin America” OR “Central America” OR developing OR “less\* developed” OR “under developed” OR underdeveloped OR “middle income” OR “low\* income” OR underserved OR “under served” OR deprived) OR TITLE-ABS-KEY (poor\* W/1 countr\* OR nation\* OR population\* OR world ) OR TITLE-ABS-KEY ((developing OR “less\* developed” OR “under developed” OR underdeveloped OR “middle income” OR “low\* income” ) W/1 econom\* )) OR TITLE-ABS-KEY (low\* W/1 gdp OR gnp OR “gross domestic” OR “gross national” ) OR TITLE-ABS-KEY (low W/3 middle W/3 countr\* ) OR TITLE-ABS-KEY ( lmic OR lmics OR “third world” OR “lami countr\*” OR “transitional countr\*” )

4. Search strings to run in Scopus: #1 AND #2 AND #3 (limited to 2000 onwards)

Inclusion criteria

Stage 1 Screening:

Inclusion criteria help in deciding whether a study that has been found is relevant. The following inclusion criteria will be applied during the first stage of the screening process (all criteria need to be satisfied for the study to be included). They will be applied to titles, then abstracts, then full text. All studies that are included on the basis of the first stage screening process, will be included in the Stage 2 screening process.

Inclusion criteria help in deciding whether a study that has been found is relevant. The following inclusion criteria should be applied (all criteria need to be satisfied for the study to be included):

1. Date: From 2000
2. Language: The review is restricted to English studies
3. Population: People that have received a cash transfer, or control households
4. Geographical locations: Low and middle income countries
5. Interventions: Conditional or unconditional cash transfers. The programmes should be non-contributory, publicly mandated or NGO-provided (so not private transfers, like remittances, or religious donations).
6. Study design: The study should be a solid empirical study (i.e. based on data and or fieldwork). Only studies that use either an experimental design or a quasi-experimental design that relies on a credible control group should be included. This includes those that demonstrate one of the following: (a) an experimental design (i.e. RCT or cluster-RCT) (b) a quasi-experimental design, including: i. regression discontinuity design ii. matching technique (e.g. propensity score matching) iii. difference-in-difference iv. interrupted time series v. other form of multivariate regression, including Instrumental Variable Technique. [Exclude studies that are theoretical; literature reviews; not descriptive or don’t have an experimental/ quasi-experimental design]
7. Outcome: health outcomes, health access, health utilisation, and nutrition Stage 2 Screening:

In the second round of screening, studies will be assessed against a range of criteria to investigate the risk of bias and reliability of findings. Specifically, studies will be assessed against the issues of selection bias, attrition bias or bias associated with interpretation of statistical significance (Type I or Type II errors). Studies that have a high risk of bias or score low on rigour will not be included in the final analysis.

List of databases used

- SCOPUS (Elsevier). This database includes 5,682 journals, conference proceedings, trade publications and book series in the Social Sciences category.
- Global Health
- POPLINE
- CAB Global Health
- Ideas-Repec

4. Snowball technique

The following four people should be contacted and asked for the five most relevant studies on the research question. We will also look at their websites for relevant publications.

1. Paul Gertler, Berkley
2. Amanda Glassman, Center for Global Development
3. Mylene Lagarde, LSHTM
4. Lucy Bassett, World Bank

Studies shared by experts will be assessed against Stage 1 and Stage 2 screening criteria. We will also check the reference lists of the studies obtained for any further studies that fit the inclusion criteria.

5. Websites searches

The following websites/search engines should be consulted, if possible using the same search strings as for the academic databases. Any studies found on these websites will be assessed against the same Stage 1 and Stage 2 screening criteria.

- Google (the first five pages)
- World Bank
- R4D DFID
- International Policy Centre for Inclusive Growth (IPC-IG)
- International Food Policy Research Institute (IFPRI)
- Poverty Action Research Lab
- FAO From Protection to Production website
- GSDRC
- OPM website
- 3iE website
- UNICEF
- Cochrane review website
- Transfer Project (UNC Chapel Hill)
- OPM website
- 3iE website
- ECLAC/CEPAL
- IADB website
- ADB website

6. Classification of studies

Studies that have passed both screening stages will be classified and described in an annotated bibliography. The classification tables will include the following information:

- authors and year of study
- geographical coverage
- detailed description of intervention and context
- population
- methods, sampling and data
- a summary of the main outcomes of the study Sub-question 1d: What is the effect of cash transfers on investment, savings and production?

1. The review research questions

The systematic literature reviews should assess the state of knowledge on the following question: *What is known about the effect of cash transfers on investment, savings and production?*

2. Methodology

The systematic literature reviews should combine three tracks. These tracks are briefly explained here and further instructions are given below.

1. **Bibliographic database search:** Searching a previously agreed upon list of academic databases, using consistent search strings (see below) that have been tested beforehand and applying inclusion/exclusion criteria.

2. **Snowball technique:** Contacting approximately three key experts in the field and asking them for recommendations for important studies on the research question. This also includes looking at the experts’ websites and publication lists and including relevant studies. Finally, we will be looking for further relevant studies in the bibliographies of the experts’ studies and recommended studies.

3. **Websites searches:** Searching previously agreed on websites (see below) for relevant studies using similar search terms as for the bibliographic databases. This also includes a google search for other grey literature.

Studies will be screened and assessed using the EPPI Reviewer software.

After an initial broad screening process that considers overall study design, as well as other broader inclusion/exclusion criteria, a second round of screening will be conducted and studies will be assessed against a range of criteria to investigate the risk of bias and reliability of findings. Specifically, studies will be assessed against the issues of selection bias, attrition bias or bias associated with interpretation of statistical significance (Type I or Type II errors). Studies that have a high risk of bias or score low on rigour will be not be included in the final analysis.

The relevant studies that make it through both stages of screening will be summarised in an annotated bibliography. The annotated bibliography lists the relevant studies in table format (see below) and briefly summarises each study in terms of relevant information on methodology, intervention and findings. More specifically, the relevant studies will also be summarised and classified in a table summarising the following information: i) publication details, (ii) description of the intervention and context, (iii) methods, data and sampling, (iv) population, v) findings of relevance to the research question including findings of statistically significant and non-significant impacts and disaggregation (e.g. by gender, age and other characteristics), and vi) contextual factors of importance.

A narrative synthesis approach will be applied to synthesise the findings. 3. Bibliographic database search

The research question

The research question is ‘What is known about the effect of cash transfers on investment, savings and production?’ Here we want to know what effects cash transfers have had on investment, assets, savings and production.

In order to understand it better, the research question can be decomposed into population, intervention and outcome:

| Population | Intervention | Outcome | |------------|--------------|---------| | People living in low or middle income countries and who either receive the intervention or are the comparison group | Conditional or unconditional cash transfers | Investment, savings and production |

| Cash transfer | Social transfer | Financial transfer | Monetary transfer | Child grant/ disability grant/ old-age grant/ social grant | Social assistance | Social pension | Non-contributory pension | Old age pension | Child benefit/ disability benefit/ old-age benefit | Basic income/ minimum income | CCT/ UCT | Income support | |---------------|-----------------|-------------------|------------------|----------------------------------------------------------|-----------------|----------------|------------------------|----------------|-----------------------------------------------|-----------------------------|---------|--------------| | Invest\* | Disinvestment | Income generat\* activities | Coping strategy | Productivity | Production | Risk | Yield | Asset | House improvement | Livestock | Smallstock | Housing | Property | Land | Tools | Equipment | Vehicle | Bicycle | Input\* | Fertil*er | Seed | Saving* | Borrow\* | Loan | Debt | Credit | Business / trade | Income-generating activity | Insurance |

The population has been restricted to people living in low and middle income countries. This includes both beneficiary and control households. The aim of the research question is to analyse the impact of cash transfers on the investment, savings and production. The outcome for this sub-question are investment, assets, savings and production. The table above also includes all synonyms that will be used in the searches.

Search strings

The search string will be composed of intervention (part 1), outcome (part 2) and country filter (example below given for SCOPUS filter). In order to capture all possible cash transfers, search strings should include all synonyms listed above. In terms of outcome, we will use investment and savings and synonyms in the search strings. The following search strings and will be used (they have been tested in the pilot phase):

1. TITLE-ABS-KEY ( “Cash transfer\*” OR “social transfer\*” OR “financial transfer\*” OR “monetary transfer\*” OR “child grant\*” OR “disability grant\*” OR “old age grant\*” OR “social grant\*” OR “basic grant\*” OR “minimum income grant\*” OR “social assistance” OR welfare OR “social pension\*” OR “non-contributory pension\*” OR “old age pension\*” OR “child benefit\*” OR “disability benefit\*” OR “old age benefit\*” OR cct OR uct OR “income support”

2. TITLE-ABS-KEY invest\* OR disinvest\* OR “coping strateg\*” OR productivity OR production OR harvest\* OR yield\* OR asset\* OR livestock OR smallstock OR hou\* OR property OR land OR tools OR equipment OR vehicle\* OR bicycle\* OR input\* OR fertilizer\* OR fertiliser\* OR seed\* OR saving\* OR borrow\* OR loan\* OR debt\* OR credit OR business\* OR trade OR insurance OR “income generat\* activit\*” OR “risk”

3. TITLE-ABS-KEY ( afghanistan OR albania OR algeria OR angola OR argentina OR armenia OR armenian OR aruba OR azerbaijan OR bangladesh OR benin OR belarus OR byelorussian OR belarus OR belorussian OR belorussia OR belize OR bhutan OR bolivia OR bosnia OR herzegovina OR hercegovina OR botswana OR brasil OR brazil OR bulgaria OR “Burkina Faso” OR “Burkina Fasso” OR “Upper Volta” OR burundi OR urundi OR cambodia OR “Khmer Republic” OR kampuchea OR cameroon OR cameroons OR cameron OR camorons OR “Cape Verde” OR “Central African Republic” OR chad OR china OR colombia OR comoros OR “Comoro Islands” OR comores OR mayotte OR congo OR zaire OR “Costa Rica\*” OR “Cote d’Ivoire” OR “Ivory Coast” OR cuba OR djibouti OR “French Somalliland” OR dominica OR “Dominican Republic” OR “East Timor” OR “East Timur” OR “Timor Leste” OR ecuador OR egypt OR “United Arab Republic” OR “El Salvador” OR eritrea OR ethiopia OR fiji OR gabon OR “Gabonese Republic” OR gambia OR gaza OR “Georgia Republic” OR “Georgian Republic” OR ghana OR grenada OR guatemala OR guinea OR guiana OR guyana OR haiti OR hungary OR honduras OR india OR maldives OR indonesia OR iran OR iraq OR jamaica OR jordan OR kazakhstan OR kazakh OR keny OR kiribati OR korea OR kosovo OR kyrgyzstan OR kirghizia OR “Kyrgyz Republic” OR kirghiz OR kirgizstan OR “Lao PDR” OR laos OR lebanon OR lesotho OR basutoland OR liberia OR libya OR macedonia OR madagascar OR “Malagasy Republic” OR malaysia OR malaya OR malay OR sabah OR sarawak OR malawi OR mali OR “Marshall Islands” OR mauritania OR mauritius OR “Agalega Islands” OR mexico OR micronesia OR “Middle East” OR moldova OR moldavia OR moldovan OR mongolia OR montenegro OR morocco OR ifni OR mozambique OR myanmar OR myanmar OR burma OR namibia OR nepal OR “Netherlands Antilles” OR “New Caledonia” OR nicaragua OR niger OR nigeria OR pakistan OR palau OR palestine OR panama OR paraguay OR peru OR philippines OR philippines OR philippines OR “Puerto Ric\*” OR romania OR rumania OR roumania OR rwanda OR ruanda OR “Saint Lucia” OR “St Lucia” OR “Saint Vincent” OR “St Vincent” OR grenadines OR samoan OR “Samoan Islands” OR “Navigator Island” OR “Navigator Islands” OR “Sao Tome” OR senegal OR serbia OR montenegro OR seychelles OR “Sierra Leone” OR “Sri Lanka” OR “Solomon Islands” OR somalia OR “South Africa” OR sudan OR suriname OR surinam OR swaziland OR syria OR tajikistan OR tajikistan OR tadjikistan OR tadjik OR tanzania OR thailand OR togo OR togoles republic OR tonga OR tunisia OR turkey OR turkmenistan OR turkmen OR uganda OR ukraine OR uzbekistan OR uzbek OR vanuatu OR “New Hebrides” OR venezuela OR vietnam OR “Viet Nam” OR “West Bank” OR yemen OR yugoslavia OR zambia OR zimbabwe ) OR TITLE-ABS-KEY ( “Developing Countries” OR africa OR asia OR caribbean OR “West Indies” OR “South America” OR “Latin America” OR “Central America” OR developing OR “less\* developed” OR “under developed” OR underdeveloped OR “middle income” OR “low\* income” OR underserved OR “under served” OR deprived ) OR TITLE-ABS-KEY ( poor\* W/1 countr\* OR nation\* OR population\* OR world ) OR TITLE-ABS-KEY ( developing OR “less\* developed” OR “under developed” OR underdeveloped OR “middle income” OR “low\* income” ) W/1 econom\* ) OR TITLE-ABS-KEY ( low\* W/1 gdp OR gnp OR “gross domestic” OR “gross national” ) OR TITLE-ABS-KEY ( low\* W/3 middle W/3 countr\* ) OR TITLE-ABS-KEY ( lmic OR lmics OR “third world” OR “lami countr\*” OR “transitional countr\*” )

4. Search strings to run in Scopus: #1 AND #2 AND #3 (limited to 2000 onwards) Inclusion criteria

Stage 1 Screening:

Inclusion criteria help in deciding whether a study that has been found is relevant. The following inclusion criteria will be applied during the first stage of the screening process (all criteria need to be satisfied for the study to be included). They will be applied to titles, then abstracts, then full text. All studies that are included on the basis of the first stage screening process, will be included in the Stage 2 screening process.

1. Date: From 2000
2. Language: The review is restricted to English studies
3. Population: People that have received a cash transfer, or control households
4. Geographical locations: Low and middle income countries
5. Interventions: Conditional or unconditional cash transfers. The programmes should be non-contributory, publicly mandated or NGO-provided (so not private transfers, like remittances, or religious donations).
6. Study design: The study should be a solid empirical study (i.e. based on data and or fieldwork). Only studies that use either an experimental design or a quasi-experimental design that relies on a credible control group should be included. This includes those that demonstrate one of the following: (a) an experimental design (i.e. RCT or cluster-RCT) (b) a quasi-experimental design, including: i. regression discontinuity design ii. matching technique (e.g. propensity score matching) iii. difference-in-difference iv. interrupted time series v. other form of multivariate regression, including Instrumental Variable Technique. [Exclude studies that are theoretical; literature reviews; not descriptive or don’t have an experimental/ quasi-experimental design]
7. Outcome: Investment, assets and savings

Stage 2 Screening:

In the second round of screening, studies will be will be assessed against a range of criteria to investigate the risk of bias and reliability of findings. Specifically, studies will be assessed against the issues of selection bias, attrition bias or bias associated with interpretation of statistical significance (Type I or Type II errors). Studies that have a high risk of bias or score low on rigour will be not be included in the final analysis.

List of databases used

- SCOPUS (Elsevier). This database includes 5,682 journals, conference proceedings, trade publications and book series in the Social Sciences category.
- AGRIS: Agricultural database
- AgEcon database
- CAB Abstracts
- IDEAS-Repec

4. Snowball technique

The following three people should be contacted and asked for the five most relevant studies on the research question. We will also look at their websites for relevant publications.

1. Benjamin Davis, FAO
2. Michelle Adato, IFPRI
3. Rachel Slater, ODI

Studies shared by experts will be assessed against Stage 1 and Stage 2 screening criteria. We will also check the reference lists of the studies obtained for any further studies that fit the inclusion criteria.

5. Websites searches

The following websites/search engines should be consulted, if possible using the same search strings as for the academic databases. Any studies found on these websites will be assessed against the same Stage 1 and Stage 2 screening criteria.

- Google (the first five pages)
- World Bank
- R4D DFID
- International Policy Centre for Inclusive Growth (IPC-IG)
- International Food Policy Research Institute (IFPRI)
- Poverty Action Research Lab
- FAO From Protection to Production website
- GSDRC
- OPM website
- 3iE website
- Transfer Project (UNC Chapel Hill)
- GSDRC
- OPM website
- ECLAC/CEPAL
- IADB website
- ADB website
- IDS website
- BLDS website
- Social Science Research Network

6. Classification of studies

Studies that have passed both screening stages will be classified and described in an annotated bibliography. The classification tables will include the following information:

- authors and year of study
- geographical coverage
- detailed description of intervention and context
- population
- methods, sampling and data
- a summary of the main outcomes of the study Sub-question 1e: What is the effect of cash transfers on employment and the labour market?

1. The review research questions

The systematic literature reviews should assess the state of knowledge on the following question: *What is known about the effect of cash transfers on employment and the labour market?*

2. Methodology

The systematic literature reviews should combine three tracks. These tracks are briefly explained here and further instructions are given below.

1. **Bibliographic database search:** Searching a previously agreed upon list of academic databases, using consistent search strings (see below) that have been tested beforehand and applying inclusion/exclusion criteria.

2. **Snowball technique:** Contacting approximately three key experts in the field and asking them for recommendations for important studies on the research question. This also includes looking at the experts’ websites and publication lists and including relevant studies. Finally, we will be looking for further relevant studies in the bibliographies of the experts’ studies and recommended studies.

3. **Websites searches:** Searching previously agreed on websites (see below) for relevant studies using similar search terms as for the bibliographic databases. This also includes a google search for other grey literature.

Studies will be screened and assessed using the EPPI Reviewer software.

After an initial broad screening process that considers overall study design, as well as other broader inclusion/exclusion criteria, a second round of screening will be conducted and studies will be assessed against a range of criteria to investigate the risk of bias and reliability of findings. Specifically, studies will be assessed against the issues of selection bias, attrition bias or bias associated with interpretation of statistical significance (Type I or Type II errors). Studies that have a high risk of bias or score low on rigour will be not be included in the final analysis.

The relevant studies that make it through both stages of screening will be summarised in an annotated bibliography. The annotated bibliography lists the relevant studies in table format (see below) and briefly summarises each study in terms of relevant information on methodology, intervention and findings. More specifically, the relevant studies will also be summarised and classified in a table summarising the following information: i) publication details, (ii) description of the intervention and context, (iii) methods, data and sampling, (iv) population, v) findings of relevance to the research question including findings of statistically significant and non-significant impacts and disaggregation (e.g. by gender, age and other characteristics), and vi) contextual factors of importance.

A narrative synthesis approach will be applied to synthesise the findings. 3. Bibliographic database search

The research question

The research question is ‘What is known about the effects of cash transfers on employment?’ Here we want to know the effect of cash transfers on labour supply.

In order to understand it better, the research question can be decomposed into population, intervention and outcome:

| Population | Intervention | Outcome | |------------|--------------|---------| | People living in low or middle income countries and who either receive the intervention or are the comparison group | Conditional or unconditional cash transfers | Employment |

| Cash transfer | Social transfer | Financial transfer | Monetary transfer | Child grant/ disability grant/ old-age grant/ social grant | Social assistance | Social pension | Non-contributory pension | Old age pension | Child benefit/ disability benefit/ old-age benefit | Basic income/ minimum income | UCT/ CCT | Income support | |---------------|----------------|-------------------|------------------|----------------------------------------------------------|-----------------|----------------|------------------------|----------------|------------------------------------------------|-----------------------------|----------|---------------| | Employment | Labo\* supply | Labo\* demand | Hiring | Job\* | Work | workforce | Labo\* market | Labo\* participation | Labo\* allocation | Number of hours worked | Informal\* | Formalisation | Migration | | | | | | | | | | | | | | | Time allocation | | | | | | | | | | | | | | | Child care | | | | | | | | | | | | | | | Child labo\* | | | | | | | | | | | | | | | Wage | | | | | | | | | | | | | | | Income | | | | | | | | | | | | | | | Salary | | | | | | | | | | | | | | | Earning | | | | | | | | | | | | | | | Diversification of income sources | | | | | | | | | | | | | | | Retirement | | | | | | | | | | | | | | | Pension age |

The population has been restricted to people living in low and middle income countries. This includes both beneficiary and control households. The aim of the research question is to analyse the impact of cash transfers on employment. The outcome for this sub-question is employment. The table above also includes all synonyms that will be used in the searches.

Search strings

The search string will be composed of intervention (part 1), outcome (part 2) and country filter (example below given for SCOPUS filter). In order to capture all possible cash transfers, search strings should include all synonyms listed above. In terms of outcome, we will use employment and synonyms in the search strings. The following search strings will be used (they have been tested in the pilot phase):

1. TITLE-ABS-KEY ( “Cash transfer\*” OR “social transfer\*” OR “financial transfer\*” OR “monetary transfer\*” OR “child grant\*” OR “disability grant\*” OR “old age grant\*” OR “social grant\*” OR “basic grant\*” OR “minimum income grant\*” OR “social assistance” OR welfare OR “social pension\*” OR “non-contributory pension\*” OR “old age pension\*” OR “child benefit\*” OR “disability benefit\*” OR “old age benefit\*” OR cct OR uct OR “income support” )

2. TITLE-ABS-KEY employ\* OR labour W/1 (supply OR demand OR participation OR allocation) OR labor W/1 (supply OR demand OR participation OR allocation) OR hiring OR hire\* OR job\* OR work OR workforce OR “labour market” OR “labor market” OR “hours worked” OR “working hours” OR informal\* OR formalisation OR formalization OR migrat\* OR migrant\* OR time W/1 allocation OR “child care” OR “child labour” OR “child labor” OR wage\* OR income OR salar\* OR earn\* OR diversif\* OR retire\* OR “pension age”

3. TITLE-ABS-KEY ( afghanistan OR albania OR algeria OR angola OR argentina OR armenia OR armenian OR aruba OR azerbaijan OR bangladesh OR benin OR byelarus OR byelorussian OR belarus OR belorussian OR belorussia OR belize OR bhutan OR bolivia OR bosnia OR herzegovina OR hercegovina OR botswana OR brasil OR brazil OR bulgaria OR “Burkina Faso” OR “Burkina Fasso” OR “Upper Volta” OR burundi OR urundi OR cambodia OR “Khmer Republic” OR kampuchea OR cameroon OR cameroons OR cameron OR camorons OR “Cape Verde” OR “Central African Republic” OR chad OR china OR colombia OR comoros OR “Comoro Islands” OR comores OR mayotte OR congo OR zaire OR “Costa Rica” OR “Cote d’Ivoire” OR “Ivory Coast” OR cuba OR djibouti OR “French Somaliland” OR dominica OR “Dominican Republic” OR “East Timor” OR “East Timur” OR “Timor Leste” OR ecuador OR egypt OR “United Arab Republic” OR “El Salvador” OR eritrea OR ethiopia OR fiji OR gabon OR “Gabonese Republic” OR gambia OR “Georgia Republic” OR “Georgian Republic” OR ghana OR grenada OR guatemala OR guinea OR guiana OR guyana OR haiti OR hungary OR honduras OR india OR maldives OR indonesia OR iran OR iraq OR jamaica OR jordan OR kazakhstan OR kazakh OR keny OR kiribati OR korea OR kosovo OR krygyzstan OR kirghizia OR “Kyrrgyz Republic” OR kirghiz OR kirgizstan OR “Lao PDR” OR laos OR lebanon OR lesotho OR hasutoland OR libera OR libya OR macedonia OR madagascar OR “Malagasy Republic” OR malaysia OR malaya OR malay OR sabah OR sarawak OR malawi OR mali OR “Marshall Islands” OR mauritania OR mauritius OR “Agalega Islands” OR mexico OR micronesia OR “Middle East” OR moldova OR moldovia OR mongolia OR montenegro OR morocco OR ifni OR mozambique OR myanmar OR myanmar OR burma OR namibia OR nepal OR “Netherlands Antilles” OR “New Caledonia” OR nicaragua OR niger OR nigeria OR pakistan OR palau OR palestine OR panama OR paraguay OR peru OR philippines OR philippines OR philippines OR “Puerto Ric\*” OR romania OR rumania OR roumania OR rwanda OR ruanda OR “Saint Lucia” OR “St Lucia” OR “Saint Vincent” OR “St Vincent” OR grenadines OR samoa OR “Samoa Islands” OR “Navigator Island” OR “Navigator Islands” OR “Sao Tome” OR senegal OR serbia OR montenegro OR seychelles OR “Sierra Leone” OR “Sri Lanka” OR “Solomon Islands” OR somalia OR “South Africa” OR sudan OR suriname OR surinam OR swaziland OR syria OR tajikistan OR tadzhikistan OR tadzikistan OR tadzhik OR tanzania OR thailand OR togo OR togoles republic OR tonga OR tunisia OR turkey OR turkmenistan OR turkmen OR uganda OR ukraine OR uzbekistan OR uzbek OR vanuatu OR “New Hebrides” OR venezuela OR vietnam OR “Viet Nam” OR “West Bank” OR yemen OR yugoslavia OR zambia OR zimbabwe ) OR TITLE-ABS-KEY ( “Developing Countries” OR africa OR asia OR caribbean OR “West Indies” OR “South America” OR “Latin America” OR “Central America” OR developing OR “less\* developed” OR “under developed” OR underdeveloped OR “middle income” OR “low\* income” OR underserved OR “under served” OR deprived ) OR TITLE-ABS-KEY ( poor\* W/1 countr\* OR nation\* OR population\* OR world ) OR TITLE-ABS-KEY ( developing OR “less\* developed” OR “under developed” OR underdeveloped OR “middle income” OR “low\* income” ) W/1 econom\* ) OR TITLE-ABS-KEY ( low\* W/1 gdp OR gnp OR “gross domestic” OR “gross national” ) OR TITLE-ABS-KEY ( low W/3 middle W/3 countr\* ) OR TITLE-ABS-KEY ( lmic OR lmics OR “third world” OR “lami countr\*” OR “transitional countr\*” )

4. Search strings to run in Scopus: #1 AND #2 AND #3 (limited to 2000 onwards) Inclusion criteria

Stage 1 Screening:

Inclusion criteria help in deciding whether a study that has been found is relevant. The following inclusion criteria will be applied during the first stage of the screening process (all criteria need to be satisfied for the study to be included). They will be applied to titles, then abstracts, then full text. All studies that are included on the basis of the first stage screening process, will be included in the Stage 2 screening process.

1. Date: From 2000
2. Language: The review is restricted to English studies
3. Population: People that have received a cash transfer, or control households
4. Geographical locations: Low and middle income countries
5. Interventions: Conditional or unconditional cash transfers. The programmes should be non-contributory, publicly mandated or NGO-provided (so not private transfers, like remittances, or religious donations).
6. Study design: The study should be a solid empirical study (i.e. based on data and or fieldwork). Only studies that use either an experimental design or a quasi-experimental design that relies on a credible control group should be included. This includes those that demonstrate one of the following: (a) an experimental design (i.e. RCT or cluster-RCT) (b) a quasi-experimental design, including: i. regression discontinuity design ii. matching technique (e.g. propensity score matching) iii. difference-in-difference iv. interrupted time series v. other form of multivariate regression, including Instrumental Variable Technique.

[Exclude studies that are theoretical; literature reviews; not descriptive or don’t have an experimental/ quasi-experimental design] 7. Outcome: Employment/ labour supply

Stage 2 Screening:

In the second round of screening, studies will be will be assessed against a range of criteria to investigate the risk of bias and reliability of findings. Specifically, studies will be assessed against the issues of selection bias, attrition bias or bias associated with interpretation of statistical significance (Type I or Type II errors). Studies that have a high risk of bias or score low on rigour will be not be included in the final analysis.

List of databases used

- SCOPUS (Elsevier). This database includes 5,682 journals, conference proceedings, trade publications and book series in the Social Sciences category.
- Econlit
- ILO Labordoc
- IDEAS-Repec

4. Snowball technique

The following five people should be contacted and asked for the five most relevant studies on the research question. We will also look at their websites for relevant publications.

1. Francesca Bastagli, ODI
2. Anna McCord, ODI
3. Fabio Veras Soares, IPC
4. Benjamin Davis, FAO
5. Christina Behrendt, ILO

Studies shared by experts will be assessed against Stage 1 and Stage 2 screening criteria. We will also check the reference lists of the studies obtained for any further studies that fit the inclusion criteria.

5. Websites searches

The following websites/search engines should be consulted, if possible using the same search strings as for the academic databases. Any studies found on these websites will be assessed against the same Stage 1 and Stage 2 screening criteria.

- Google (the first five pages)
- World Bank
- R4D DFID
- International Policy Centre for Inclusive Growth (IPC-IG)
- International Food Policy Research Institute (IFPRI)
- Poverty Action Research Lab
- FAO From Protection to Production website
- GSDRC
- OPM website
- 3iE website
- ILO website
- FAO From Protection to Production website
- Transfer Project (UNC Chapel Hill)
- ECLAC/CEPAL
- IADB website
- ADB website
- IDS website
- BLDS website
- Social Science Research Network

6. Classification of studies

Studies that have passed both screening stages will be classified and described in an annotated bibliography. The classification tables will include the following information:

- authors and year of study
- geographical coverage
- detailed description of intervention and context
- population
- methods, sampling and data
- a summary of the main outcomes of the study Sub-question 1f: What is the effect of cash transfers on empowerment?

1. The review research questions

The systematic literature reviews should assess the state of knowledge on the following question: *What is known about the effect of cash transfers on social empowerment, political empowerment and psycho-social wellbeing?*

2. Methodology

The systematic literature reviews should combine three tracks. These tracks are briefly explained here and further instructions are given below.

1. **Bibliographic database search:** Searching a previously agreed upon list of academic databases, using consistent search strings (see below) that have been tested beforehand and applying inclusion/exclusion criteria.

2. **Snowball technique:** Contacting approximately four key experts in the field and asking them for recommendations for important studies on the research question. This also includes looking at the experts’ websites and publication lists and including relevant studies. Finally, we will be looking for further relevant studies in the bibliographies of the experts’ studies and recommended studies.

3. **Websites searches:** Searching previously agreed on websites (see below) for relevant studies using similar search terms as for the bibliographic databases. This also includes a google search for other grey literature.

Studies will be screened and assessed using the EPPI Reviewer software. After an initial broad screening process that considers overall study design, as well as other broader inclusion/exclusion criteria, a second round of screening will be conducted and studies will be assessed against a range of criteria to investigate the risk of bias and reliability of findings. Specifically, studies will be assessed against the issues of selection bias, attrition bias or bias associated with interpretation of statistical significance (Type I or Type II errors). Studies that have a high risk of bias or score low on rigour will be not be included in the final analysis.

The relevant studies that make it through both stages of screening will be summarised in an annotated bibliography. The annotated bibliography lists the relevant studies in table format (see below) and briefly summarises each study in terms of relevant information on methodology, intervention and findings. More specifically, the relevant studies will also be summarised and classified in a table summarising the following information: i) publication details, (ii) description of the intervention and context, (iii) methods, data and sampling, (iv) population, v) findings of relevance to the research question including findings of statistically significant and non-significant impacts and disaggregation (e.g. by gender, age and other characteristics), and vi) contextual factors of importance.

A narrative synthesis approach will be applied to synthesise the findings. 3. Bibliographic database search

The research question

The research question is ‘What is known about the effect of cash transfers on empowerment?’ Here we want to know about the effects on social empowerment, political empowerment and psycho-social wellbeing.

In order to understand it better, the research question can be decomposed into population, intervention and outcome:

| Population | Intervention | Outcome | |------------|--------------|---------| | People living in low or middle income countries and who either receive the intervention or are the comparison group | Conditional or unconditional cash transfers | Social empowerment, political empowerment and psycho-social wellbeing | | Cash transfer | Empowerment | | Social transfer | Decision making | | Financial transfer | Voice | | Monetary transfer | Confidence | | Child grant/ disability grant/ old-age grant/ social grant | Violence | | Social assistance | Choice | | Social pension | Control | | Non-contributory pension | Power | | Old age pension | Political participation | | Child benefit/ disability benefit/ old-age benefit | Community meeting | | Basic income/ minimum income | Social audit | | UCT/ CCT | Participatory monitoring | | Income support | Community Score Card | | | Gender relations | | | Relationship\* | | | Dynamics | | | Social inclusion | | | Social exclusion | | | Mobility | | | Discrimination | | | Pride | | | Dignity | | | Social capital | | | Social network\* | | | Social participation | | | Stigma | | | Acceptance | | | Respect | | | Self-esteem | | | Reciprocity | | | Informal transfer | | | Child / early/ forced marriage | | | Sexual debut | | | Eating order |

The population has been restricted to people living in low and middle income countries. This includes both beneficiary and control households. The aim of the research question is to analyse the impact of cash transfers on empowerment. The outcome for this sub-question are economic empowerment, social empowerment, political empowerment and social relations. The table above also includes all synonyms that will be used in the searches.

Search strings

The search string will be composed of intervention (part 1), outcome (part 2) and country filter (example below given for SCOPUS filter). In order to capture all possible cash transfers, search strings should include all synonyms listed above. In terms of outcome, we will use economic empowerment, social empowerment, political empowerment and social relations and synonyms in the search strings. The following search strings and will be used (they have been tested in the pilot phase): Cash transfers: what does the evidence say?

1. TITLE-ABS-KEY ( “Cash transfer\*” OR “social transfer\*” OR “financial transfer\*” OR “monetary transfer\*” OR “child grant\*” OR “disability grant\*” OR “old age grant\*” OR “social grant\*” OR “basic grant\*” OR “minimum income grant\*” OR “social assistance” OR welfare OR “social pension\*” OR “non-contributory pension\*” OR “old age pension\*” OR “child benefit\*” OR “disability benefit\*” OR “old age benefit\*” OR cct OR uct OR “income support” )

2. TITLE-ABS-KEY (empower\* OR “decision making” OR confiden\* OR violen\* OR power\* OR voice\* OR choice\* OR control OR “political participation” OR “community participation” OR “social audit\*” OR “participatory monitoring” OR “community score card\*” OR relation\* OR dynamic\* OR “social inclusion” OR “social exclusion” OR discrimination OR pride OR dignity OR “social capital” OR stigma OR “social network\*” OR “social relation\*” OR “social inclusion” OR “social exclusion” OR discrimination OR “social audit\*” OR “participatory monitoring” OR “community score card\*” OR voice\* OR choice\* OR control OR “political participation” OR “community meeting\*” OR “child marriage\*” OR “early marriage\*” OR “forced marriage\*” OR “sexual debut” OR mobility OR “eating order”)

3. TITLE-ABS-KEY ( afghanistan OR albania OR algeria OR angola OR argentina OR armenia OR armenian OR aruba OR azerbaijan OR bangladesh OR benin OR byelarus OR byelorussian OR belarus OR belorussian OR belize OR bhutan OR bolivia OR bosnia OR herzegovina OR hercegovina OR botswana OR brasil OR brazil OR bulgaria OR “Burkina Faso” OR “Burkina Fasso” OR “Upper Volta” OR burundi OR urundi OR cambodia OR “Khmer Republic” OR kampuchea OR cameroon OR cameroons OR cameron OR camoros OR “Comoro Islands” OR comores OR mayotte OR congo OR zaire OR “Costa Rica” OR “Cote d’Ivoire” OR “Ivory Coast” OR cuba OR djibouti OR “French Somaliland” OR dominica OR “Dominican Republic” OR “East Timor” OR “East Timur” OR “Timor Leste” OR ecuador OR egypt OR “United Arab Republic” OR “El Salvador” OR eritrea OR ethiopia OR fiji OR gabon OR “Gabonese Republic” OR gambia OR gaza OR “Georgia Republic” OR “Georgian Republic” OR ghana OR grenada OR guatemala OR guinea OR guiana OR guyana OR haiti OR hungary OR honduras OR india OR maldives OR indonesia OR iran OR iraq OR jamaica OR jordan OR kazakhstan OR kazakh OR kenya OR kiribati OR korea OR kosovo OR krygyzstan OR kirghizia OR “Kyrgyz Republic” OR kirghiz OR kirgizstan OR “Lao PDR” OR laos OR lebanon OR lesotho OR basutoland OR libera OR libya OR macedonia OR madagascar OR “Malagasy Republic” OR malaysia OR malay OR sahara OR sarawak OR malawi OR mali OR “Marshall Islands” OR mauritania OR mauritius OR “Agalega Islands” OR mexico OR micronesia OR “Middle East” OR moldova OR moldova OR moldovian OR mongolia OR montenegro OR morocco OR ifni OR mozambique OR myanmar OR myanmar OR burma OR namibia OR nepal OR “Netherlands Antilles” OR “New Caledonia” OR nicaragua OR niger OR nigeria OR pakistan OR palau OR palestine OR panama OR paraguay OR peru OR philippines OR philippines OR philippines OR philippines OR “Puerto Ric\*” OR romania OR rumania OR roumania OR rwanda OR ruanda OR “Saint Lucia” OR “St Lucia” OR “Saint Vincent” OR “St Vincent” OR grenadines OR samoan OR “Samoa Islands” OR “Nauru Island” OR “Nauru Islands” OR “Sao Tome” OR “Senegal” OR serbia OR montenegro OR seychelles OR “Sierra Leone” OR “Sri Lanka” OR “Solomon Islands” OR somalia OR “South Africa” OR sudan OR suriname OR surinam OR swaziland OR syria OR tajikistan OR tajikistan OR tadjikistan OR tadjik OR tanzania OR thailand OR togo OR togoles republic OR tonga OR tunisia OR turkey OR turkmenistan OR turkmen OR uganda OR ukraine OR uzbekistan OR uzbek OR vanuatu OR “New Hebrides” OR venezuela OR vietnam OR “Viet Nam” OR “West Bank” OR yemen OR yugoslavia OR zambia OR zimbabwe ) OR TITLE-ABS-KEY ( “Developing Countries” OR africa OR asia OR caribbean OR “West Indies” OR “South America” OR “Latin America” OR “Central America” OR developing OR “less\* developed” OR “under developed” OR underdeveloped OR “middle income” OR “low\* income” OR underserved OR “under served” OR deprived ) OR TITLE-ABS-KEY ( poor\* W/1 countr\* OR nation\* OR population\* OR world ) OR TITLE-ABS-KEY ( developing OR “less\* developed” OR “under developed” OR underdeveloped OR “middle income” OR “low\* income” ) W/1 econom\* ) OR TITLE-ABS-KEY ( low\* W/1 gdp OR gnp OR “gross domestic” OR “gross national” ) OR TITLE-ABS-KEY (low W/3 middle W/3 countr\* ) OR TITLE-ABS-KEY ( lmic OR lmics OR “third world” OR “lami countr\*” OR “transitional countr\*” )

4. Search strings to run in Scopus: #1 AND #2 AND #3 (limited to 2000 onwards)

**Inclusion criteria**

**Stage 1 Screening:**

Inclusion criteria help in deciding whether a study that has been found is relevant. The following inclusion criteria will be applied during the first stage of the screening process (all criteria need to be satisfied for the study to be included). They will be applied to titles, then abstracts, then full text. All studies that are included on the basis of the first stage screening process, will be included in the Stage 2 screening process.

1. **Date:** From 2000

2. **Language:** The review is restricted to English studies

3. **Population:** People that have received a cash transfer, or control households

4. **Geographical locations:** Low and middle income countries

5. **Interventions:** Conditional or unconditional cash transfers. The programmes should be non-contributory, publicly mandated or NGO-provided (so not private transfers, like remittances, or religious donations).

6. **Study design:** The study should be a solid empirical study (i.e. based on data and or fieldwork). Only studies that use either an experimental design or a quasi-experimental design that relies on a credible control group should be included. This includes those that demonstrate one of the following: (a) an experimental design (i.e. RCT or cluster-RCT) (b) a quasi-experimental design, including: i. regression discontinuity design ii. matching technique (e.g. propensity score matching) iii. difference-in-difference iv. interrupted time series v. other form of multivariate regression, including Instrumental Variable Technique.

   [Exclude studies that are theoretical; literature reviews; not descriptive or don’t have an experimental/ quasi-experimental design]

7. **Outcome:** Social empowerment; economic empowerment; psycho-social wellbeing

**Stage 2 Screening:**

In the second round of screening, studies will be assessed against a range of criteria to investigate the risk of bias and reliability of findings. Specifically, studies will be assessed against the issues of selection bias, attrition bias or bias associated with interpretation of statistical significance (Type I or Type II errors). Studies that have a high risk of bias or score low on rigour will be not be included in the final analysis.

**List of databases used**

- SCOPUS (Elsevier). This database includes 5,682 journals, conference proceedings, trade publications and book series in the Social Sciences category.
- IDEAS-Repec

4. Snowball technique

The following four people should be contacted and asked for the five most relevant studies on the research question. We will also look at their websites for relevant publications.

1. Maxime Molyneux, UCL
2. Nicola Jones, ODI
3. Babken Babajanian, LSE
4. Christina Behrendt, ILO

Studies shared by experts will be assessed against Stage 1 and Stage 2 screening criteria. We will also check the reference lists of the studies obtained for any further studies that fit the inclusion criteria.

5. Websites searches

The following websites/search engines should be consulted, if possible using the same search strings as for the academic databases. Any studies found on these websites will be assessed against the same Stage 1 and Stage 2 screening criteria.

- Google (the first five pages)
- World Bank
- R4D DFID
- International Policy Centre for Inclusive Growth (IPC-IG)
- International Food Policy Research Institute (IFPRI)
- Poverty Action Research Lab
- FAO From Protection to Production website
- GSDRC
- OPM website
- 3iE website
- FAO From Protection to Production website
- Transfer Project (UNC Chapel Hill)
- ECLAC/CEPAL
- IADB website
- ADB website
- IDS website
- BLDS website
- Social Science Research Network

6. Classification of studies

Studies that have passed both screening stages will be classified and described in an annotated bibliography. The classification tables will include the following information:

- authors and year of study
- geographical coverage
- detailed description of intervention and context
- population
- methods, sampling and data
- a summary of the main outcomes of the study Sub-question 2a: What is the effect of core cash transfer design parameters on programme outcomes?

1. The review research questions

The systematic literature reviews should assess the state of knowledge on the following question: *What is known about the effect of core cash transfer design parameters on programme outcomes?*

2. Methodology

The systematic literature reviews should combine three tracks. These tracks are briefly explained here and further instructions are given below.

1. **Bibliographic database search:** Searching a previously agreed upon list of academic databases, using consistent search strings (see below) that have been tested beforehand and applying inclusion/exclusion criteria.

2. **Snowball technique:** Contacting approximately three key experts in the field and asking them for recommendations for important studies on the research question. This also includes looking at the experts’ websites and publication lists and including relevant studies. Finally, we will be looking for further relevant studies in the bibliographies of the experts’ studies and recommended studies.

3. **Websites searches:** Searching previously agreed on websites (see below) for relevant studies using similar search terms as for the bibliographic databases. This also includes a google search for other grey literature.

Studies will be screened and assessed using the EPPI Reviewer software. After an initial broad screening process that considers overall study design, as well as other broader inclusion/exclusion criteria, a second round of screening will be conducted. The second stage assessment will depend on the type of study. In the case of impact evaluation studies, the same assessment tool used for those studies retrieved in research question one will be applied. In the case of qualitative and descriptive studies and institutional analysis, an assessment of methodological rigour based on the literature around evaluating qualitative studies will be applied.

The relevant studies that make it through both stages of screening will be summarised in an annotated bibliography. The annotated bibliography lists the relevant studies in table format (see below) and briefly summarises each study in terms of relevant information on methodology, intervention and findings. More specifically, the relevant studies will also be summarised and classified in a table summarising the following information: i) publication details, (ii) description of the intervention and context, (iii) methods, data and sampling, (iv) population, v) findings of relevance to the research question including findings of statistically significant and non-significant impacts and disaggregation (e.g. by gender, age and other characteristics), and vi) contextual factors of importance.

A narrative synthesis approach will be applied to synthesise the findings. 3. Bibliographic database search

The research question

The research question is ‘What is known about the effect of core cash transfer design parameters on programme outcomes?’ Here we want to know whether transfer amount, transfer duration, transfer frequency, and transfer recipient mediates programme impacts.

In order to understand it better, the research question can be decomposed into population, intervention and design/implementation factor:

| Population | Intervention | Design/ implementation factor | |------------|--------------|-------------------------------| | People living in low or middle income countries and who either receive the intervention or are the comparison group | Conditional or unconditional cash transfers | Core cash transfer design parameters | | | Cash transfer | Transfer level / Transfer amount / Transfer size | | | Social transfer | Payment size / payment level / payment amount | | | Financial transfer | Maximum duration | | | Monetary transfer | Time limit | | | Child grant/ disability grant/ old-age grant/ social grant | Eligibility | | | Social assistance | Payment frequency | | | Social pension | Recipient | | | Non-contributory pension | Beneficiary | | | Old age pension | Target group | | | Child benefit/ disability benefit/ old-age benefit | Graduation | | | Basic income/ minimum income | | | | UCT/ CCT | | | | Income support | |

The population has been restricted to people living in low and middle income countries. This includes both beneficiary and control households. The aim of the research question is to analyse the effect of cash transfer design on programme outcomes. The design/implementation factors for this sub-question are transfer amount, transfer duration, transfer frequency, and transfer recipient. The table above also includes all synonyms that will be used in the searches.

Search strings

The search string will be composed of intervention (part 1), design and implementation factor (part 2) and country filter (example below given for SCOPUS filter). In order to capture all possible cash transfers, search strings should include all synonyms listed above. In terms of design/implementation factors, we will use transfer amount, transfer duration, transfer frequency, and transfer recipient in the search strings. The following search strings and will be used (they have been tested in the pilot phase):

1. TITLE-ABS-KEY ( “Cash transfer\*” OR “social transfer\*” OR “financial transfer\*” OR “monetary transfer\*” OR “child grant\*” OR “disability grant\*” OR “old age grant\*” OR “social grant\*” OR “basic grant\*” OR “minimum income grant\*” OR “social assistance” OR “welfare” OR “social pension\*” OR “non-contributory pension\*” OR “old age pension\*” OR “child benefit\*” OR “disability benefit\*” OR “old age benefit\*” OR “cct” OR “uct” OR “income support” )

2. TITLE-ABS-KEY ( transfer\* W/1 (level\* OR amount\* OR size OR frequency\*) payment\* W/1 level\* OR amount\* OR size OR frequency\*) OR “maximum duration” OR “time limit\*” OR “eligibility” OR “graduation” OR “recipient\*” OR “beneficiary\*” OR “target group\*”)

3. TITLE-ABS-KEY ( afghanistan OR albania OR algeria OR angola OR argentina OR armenia OR armenian OR aruba OR azerbaijan OR bangladesh OR benin OR byelarus OR byelorussian OR belarus OR belorussian OR belorussia OR belize OR bhutan OR bolivia OR bosnia OR herzegovina OR hercegovina OR botswana OR brasil OR brazil OR bulgaria OR “Burkina Faso” OR “Burkina Fasso” OR “Upper Volta” OR “burundi” OR urundi OR cambodia OR “Khmer Republic” OR kampuchea OR cameroon OR... cameroons OR cameron OR cameros OR “Cape Verde” OR “Central African Republic” OR chad OR china OR colombia OR comoros OR “Comoro Islands” OR comores OR mayotte OR congo OR zaire OR “Costa Rica” OR “Cote d’Ivoire” OR “Ivory Coast” OR cuba OR djibouti OR “French Somaliland” OR dominica OR “Dominican Republic” OR “East Timor” OR “East Timur” OR “Timor Leste” OR ecuador OR egypt OR “United Arab Republic” OR “El Salvador” OR eritrea OR ethiopia OR fiji OR gabon OR “Gabonese Republic” OR gambia OR gaza OR “Georgia Republic” OR “Georgian Republic” OR ghana OR grenada OR guatemala OR guinea OR guiana OR guyana OR haiti OR hungary OR honduras OR india OR maldives OR indonesia OR iran OR iraq OR jamaica OR jordan OR kazakhstan OR kazakh OR kenya OR kiribati OR korea OR kosovo OR kyrgyzstan OR kirghizia OR “Kyrgyz Republic” OR kirghiz OR kirgizstan OR “Lao PDR” OR laos OR lebanon OR lesotho OR basutoland OR liberia OR libya OR macedonia OR madagascar OR “Malagasy Republic” OR malaysia OR malaya OR malay OR sabah OR sarawak OR malawi OR mali OR “Marshall Islands” OR mauritania OR mauritius OR “Agalega Islands” OR mexico OR micronesia OR “Middle East” OR moldova OR moldovia OR mongolia OR montenegro OR morocco OR ifni OR mozambique OR myanmar OR myanmar OR burma OR namibia OR nepal OR “Netherlands Antilles” OR “New Caledonia” OR nicaragua OR niger OR nigeria OR pakistan OR palau OR palestine OR panama OR paraguay OR peru OR philippines OR philippines OR philippines OR “Puerto Rico” OR romania OR rumania OR roumania OR rwanda OR ruanda OR “Saint Lucia” OR “St Lucia” OR “Saint Vincent” OR “St Vincent” OR grenadines OR samoan OR “Samoa Islands” OR “Navigator Island” OR “Navigator Islands” OR “Sao Tome” OR senegal OR serbia OR montenegro OR seychelles OR “Sierra Leone” OR “Sri Lanka” OR “Solomon Islands” OR somalia OR “South Africa” OR sudan OR suriname OR surinam OR swaziland OR syria OR tajikistan OR tadzhikistan OR tadzikistan OR tadjik OR tanzania OR thailand OR togo OR togoles republic OR tonga OR tunisia OR turkey OR turkmenistan OR turkmen OR uganda OR ukraine OR uzbekistan OR uzbek OR vanuatu OR “New Hebrides” OR venezuela OR vietnam OR “Viet Nam” OR “West Bank” OR yemen OR yugoslavia OR zambia OR zimbabwe ) OR TITLE-ABS-KEY ( “Developing Countries” OR africa OR asia OR caribbean OR “West Indies” OR “South America” OR “Latin America” OR “Central America” OR developing OR “less\* developed” OR “under developed” OR underdeveloped OR “middle income” OR “low\* income” OR underserved OR “under served” OR deprived ) OR TITLE-ABS-KEY ( poor\* W/1 countr\* OR nation\* OR population\* OR world ) OR TITLE-ABS-KEY ( developing OR “less\* developed” OR “under developed” OR underdeveloped OR “middle income” OR “low\* income” ) W/1 econom\* ) OR TITLE-ABS-KEY ( low\* W/1 gdp OR gnp OR “gross domestic” OR “gross national” ) OR TITLE-ABS-KEY ( low W/3 middle W/3 countr\* ) OR TITLE-ABS-KEY ( lmic OR lmics OR “third world” OR “lami countr\*” OR “transitional countr\*” )

4. Search strings to run in Scopus: #1 AND #2 AND #3 (limited to 2000 onwards) Inclusion criteria

Stage 1 Screening:

Inclusion criteria help in deciding whether a study that has been found is relevant. The following inclusion criteria will be applied during the first stage of the screening process (all criteria need to be satisfied for the study to be included). They will be applied to titles, then abstracts, then full text. All studies that are included on the basis of the first stage screening process, will be included in the Stage 2 screening process.

1. Date: From 2000
2. Language: The review is restricted to English studies
3. Population: People that have received a cash transfer, or control households
4. Geographical locations: Low and middle income countries
5. Interventions: Conditional or unconditional cash transfers. The programmes should be non-contributory, publicly mandated or NGO-provided (so not private transfers, like remittances, or religious donations).
6. Study design: The study should be a solid empirical study (i.e. based on data and or fieldwork) or an institutional analysis. It can be qualitative or quantitative. [Not theoretical; no literature review; not descriptive]
7. Design/ implementation factor: transfer amount, transfer duration, transfer frequency, and transfer recipient
8. Analysis: Design and implementation factors are explicitly linked to outcomes.

Stage 2 Screening:

The second stage assessment will depend on the type of study. In the case of impact evaluation studies, the same assessment tool used for those studies retrieved in research question one will be applied. In the case of qualitative and descriptive studies and institutional analysis, an assessment of methodological rigour based on the literature around evaluating qualitative studies will be applied.

List of databases used

- SCOPUS (Elsevier). This database includes 5,682 journals, conference proceedings, trade publications and book series in the Social Sciences category.
- IDEAS-Repec

4. Snowball technique

The following three people should be contacted and asked for the five most relevant studies on the research question. We will also look at their websites for relevant publications.

1. Rachel Slater, ODI
2. Mike Samson, EPRI
3. Margaret Grosh, World Bank

Studies shared by experts will be assessed against Stage 1 and Stage 2 screening criteria. We will also check the reference lists of the studies obtained for any further studies that fit the inclusion criteria. 5. Websites searches

The following websites/search engines should be consulted, if possible using the same search strings as for the academic databases. Any studies found on these websites will be assessed against the same Stage 1 and Stage 2 screening criteria.

- Google (the first five pages)
- World Bank
- R4D DFID
- International Policy Centre for Inclusive Growth (IPC-IG)
- International Food Policy Research Institute (IFPRI)
- GSDRC
- OPM website
- Transfer Project (UNC Chapel Hill)
- ECLAC/CEPAL
- IADB website
- ADB website
- IDS website
- BLDS website
- Social Science Research Network
- 3iE website

6. Classification of studies

Studies that have passed both screening stages will be classified and described in an annotated bibliography. The classification tables will include the following information:

- authors and year of study
- geographical coverage
- detailed description of intervention and context
- population
- methods, sampling and data
- summary findings on design and implementation factor Sub-question 2b: What is the effect of conditionality on cash transfer programme outcomes?

1. The review research questions

The systematic literature reviews should assess the state of knowledge on the following question: *What is known about the effect of conditionality on cash transfer programme outcomes?*

2. Methodology

The systematic literature reviews should combine three tracks. These tracks are briefly explained here and further instructions are given below.

1. **Bibliographic database search:** Searching a previously agreed upon list of academic databases, using consistent search strings (see below) that have been tested beforehand and applying inclusion/exclusion criteria.

2. **Snowball technique:** Contacting approximately four key experts in the field and asking them for recommendations for important studies on the research question. This also includes looking at the experts’ websites and publication lists and including relevant studies. Finally, we will be looking for further relevant studies in the bibliographies of the experts’ studies and recommended studies.

3. **Websites searches:** Searching previously agreed on websites (see below) for relevant studies using similar search terms as for the bibliographic databases. This also includes a google search for other grey literature.

Studies will be screened and assessed using the EPPI Reviewer software. After an initial broad screening process that considers overall study design, as well as other broader inclusion/exclusion criteria, a second round of screening will be conducted. The second stage assessment will depend on the type of study. In the case of impact evaluation studies, the same assessment tool used for those studies retrieved in research question one will be applied. In the case of qualitative and descriptive studies and institutional analysis, an assessment of methodological rigour based on the literature around evaluating qualitative studies will be applied.

The relevant studies that make it through both stages of screening will be summarised in an annotated bibliography. The annotated bibliography lists the relevant studies in table format (see below) and briefly summarises each study in terms of relevant information on methodology, intervention and findings. More specifically, the relevant studies will also be summarised and classified in a table summarising the following information: i) publication details, (ii) description of the intervention and context, (iii) methods, data and sampling, (iv) population, v) findings of relevance to the research question including findings of statistically significant and non-significant impacts and disaggregation (e.g. by gender, age and other characteristics), and vi) contextual factors of importance.

A narrative synthesis approach will be applied to synthesise the findings. 3. Bibliographic database search

The research question

The research question is ‘What is known about the effect of conditionality on programme outcomes?’ Here we want to know whether conditionality and type of conditionality mediates programme impacts.

In order to understand it better, the research question can be decomposed into population, intervention and design/implementation factor:

| Population | Intervention | Design/ implementation factor | |------------|--------------|------------------------------| | People living in low or middle income countries and who either receive the intervention or are the comparison group | Conditional or unconditional cash transfers | Conditionality and type of conditionality | | Cash transfer | Conditional | | Social transfer | Unconditional | | Financial transfer | Condition\* | | Monetary transfer | Compliance | | Child grant/ disability grant/ old-age grant/ social grant | Non-compliance | | Social assistance | Enforc\* | | Social pension | Sanction\* | | Non-contributory pension | Punitive | | Old age pension | Facilitative | | Child benefit/ disability benefit/ old-age benefit | Soft | | Basic income/ minimum income | Co-responsibilit\* | | UCT/ CCT | Label\* | | Income support | Contract | | | Family improvement plan |

The population has been restricted to people living in low and middle income countries. This includes both beneficiary and control households. The aim of the research question is to analyse the effect of conditionality on cash transfers outcomes. The design/implementation factors for this sub-question are conditionality and type of conditionality. The table above also includes all synonyms that will be used in the searches.

Search strings

The search string will be composed of intervention (part 1), design and implementation factor (part 2) and country filter (example below given for SCOPUS filter). In order to capture all possible cash transfers, search strings should include all synonyms listed above. In terms of design/implementation factors, we will use conditionality and type of conditionality in the search strings. The following search strings and will be used (they have been tested in the pilot phase):

1. TITLE-ABS-KEY ( “Cash transfer\*” OR “social transfer\*” OR “financial transfer\*” OR “monetary transfer\*” OR “child grant\*” OR “disability grant\*” OR “old age grant\*” OR “social grant\*” OR “basic grant\*” OR “minimum income grant\*” OR “social assistance” OR welfare OR “social pension\*” OR “non-contributory pension\*” OR “old age pension\*” OR “child benefit\*” OR “disability benefit\*” OR “old age benefit\*” OR cct OR uct OR “income support\*” )

2. TITLE-ABS-KEY (“condition\* OR unconditional OR comply OR conditionality OR non-compliance OR enforce\* OR sanction\* OR punitive OR facilitative OR soft OR co-responsibility\* OR label\* OR contract\* OR “family improvement plan\*” )

3. TITLE-ABS-KEY ( afghanistan OR albania OR algeria OR angola OR argentina OR armenia OR armenian OR aruba OR azerbaijan OR bangladesh OR benin OR byelarus OR byelorussian OR belarus OR belorussian OR belorussia OR belize OR bhutan OR bolivia OR bosnia OR herzegovina OR hercegovina OR botswana OR brasil OR brazil OR bulgaria OR “Burkina Faso” OR “Burkina Fasso” OR “Upper Volta” OR burundi OR urundi OR cambodia OR “Khmer Republic” OR kampuchea OR cameroon OR cameroons OR cameron OR cameros OR “Cape Verde” OR... “Central African Republic” OR chad OR china OR colombia OR comoros OR “Comoro Islands” OR comores OR mayotte OR congo OR zaire OR “Costa Rica\*” OR “Cote d’Ivoire” OR “Ivory Coast” OR cuba OR djibouti OR “French Somaliland” OR dominica OR “Dominican Republic” OR “East Timor” OR “East Timur” OR “Timor Leste” OR ecuador OR egypt OR “United Arab Republic” OR “El Salvador” OR eritrea OR ethiopia OR fiji OR gabon OR “Gabonese Republic” OR gambia OR gaza OR “Georgia Republic” OR “Georgian Republic” OR ghana OR grenada OR guatemala OR guinea OR guiana OR guyana OR haiti OR hungary OR honduras OR india OR maldives OR indonesia OR iran OR iraq OR jamaica OR jordan OR kazakhstan OR kazakh OR kenya OR kiribati OR korea OR kosovo OR kyrgyzstan OR kirghizia OR “Kyrgyz Republic” OR kirghiz OR kirgizstan OR “Lao PDR” OR laos OR lebanon OR lesotho OR basutoland OR liberia OR libya OR macedonia OR madagascar OR “Malagasy Republic” OR malaysia OR malaya OR malay OR sabah OR sarawak OR malawi OR mali OR “Marshall Islands” OR mauritania OR mauritius OR “Agalega Islands” OR mexico OR micronesia OR “Middle East” OR moldova OR moldovia OR moldovan OR mongolia OR montenegro OR morocco OR ifni OR mozambique OR myanmar OR myanmar OR burma OR namibia OR nepal OR “Netherlands Antilles” OR “New Caledonia” OR nicaragua OR niger OR nigeria OR pakistan OR palau OR palestine OR myanmar OR paraguay OR peru OR philippines OR philippines OR philippines OR “Puerto Rico\*” OR romania OR rumania OR rumania OR rwanda OR ruanda OR “Saint Lucia” OR “St Lucia” OR “Saint Vincent” OR “St Vincent” OR grenadines OR samoa OR “Samoan Islands” OR “Navigator Island” OR “Navigator Islands” OR “Sao Tome” OR senegal OR serbia OR montenegro OR seychelles OR “Sierra Leone” OR “Sri Lanka” OR “Solomon Islands” OR somalia OR “South Africa” OR sudan OR suriname OR surinam OR swaziland OR syria OR tajikistan OR tajikistan OR tadjikistan OR tadjik OR tanzania OR thailand OR togo OR togoles republic OR tonga OR tunisia OR turkey OR turkmenistan OR turkmen OR uganda OR ukraine OR uzbekistan OR uzbek OR vanuatu OR “New Hebrides” OR venezuela OR vietnam OR “Viet Nam” OR “West Bank” OR yemen OR yugoslavia OR zambia OR zimbabwe ) OR TITLE-ABS-KEY ( “Developing Countries” OR africa OR asia OR caribbean OR “West Indies” OR “South America” OR “Latin America” OR “Central America” OR developing OR “less\* developed” OR “under developed” OR underdeveloped OR “middle income” OR “low\* income” OR underserved OR “under served” OR deprived ) OR TITLE-ABS-KEY ( poor\* W/1 countr\* OR nation\* OR population\* OR world ) OR TITLE-ABS-KEY ( developing OR “less\* developed” OR “under developed” OR underdeveloped OR “middle income” OR “low\* income” ) W/1 econom\* ) OR TITLE-ABS-KEY ( low\* W/1 gdp OR gnp OR “gross domestic” OR “gross national” ) OR TITLE-ABS-KEY ( low W/3 middle W/3 countr\* ) OR TITLE-ABS-KEY ( lmic OR lmic\* OR “third world” OR “lami countr\*” OR “transitional countr\*” )

4. Search strings to run in Scopus: #1 AND #2 AND #3 (limited to 2000 onwards) Inclusion criteria

Stage 1 Screening:

Inclusion criteria help in deciding whether a study that has been found is relevant. The following inclusion criteria will be applied during the first stage of the screening process (all criteria need to be satisfied for the study to be included). They will be applied to titles, then abstracts, then full text. All studies that are included on the basis of the first stage screening process, will be included in the Stage 2 screening process.

1. Date: From 2000
2. Language: The review is restricted to English studies
3. Population: People that have received a cash transfer, or control households
4. Geographical locations: Low and middle income countries
5. Interventions: Conditional or unconditional cash transfers. The programmes should be non-contributory, publicly mandated or NGO-provided (so not private transfers, like remittances, or religious donations).
6. Study design: The study should be an empirical study (i.e. based on data and or fieldwork) or an institutional analysis. It can be qualitative or quantitative. [Not theoretical; no literature review; not descriptive]
7. Design/ implementation factor: conditionality and type of conditionality
8. Analysis: Design and implementation factors are explicitly linked to outcomes.

Stage 2 Screening:

The second stage assessment will depend on the type of study. In the case of impact evaluation studies, the same assessment tool used for those studies retrieved in research question one will be applied. In the case of qualitative and descriptive studies and institutional analysis, an assessment of methodological rigour based on the literature around evaluating qualitative studies will be applied.

List of databases used

- SCOPUS (Elsevier). This database includes 5,682 journals, conference proceedings, trade publications and book series in the Social Sciences category.
- IDEAS Repec

4. Snowball technique

The following four people should be contacted and asked for the five most relevant studies on the research question. We will also look at their websites for relevant publications.

1. Berk Ozler, World Bank
2. Ariel Fiszbein, World Bank
3. Norbert Schady, IDB
4. Orazio Attanasio, UCL

Studies shared by experts will be assessed against Stage 1 and Stage 2 screening criteria. We will also check the reference lists of the studies obtained for any further studies that fit the inclusion criteria. 5. Websites searches

The following websites/search engines should be consulted, if possible using the same search strings as for the academic databases. Any studies found on these websites will be assessed against the same Stage 1 and Stage 2 screening criteria.

- Google (the first five pages)
- World Bank
- R4D DFID
- International Policy Centre for Inclusive Growth (IPC-IG)
- International Food Policy Research Institute (IFPRI)
- GSDRC
- OPM website
- Transfer Project (UNC Chapel Hill)
- ECLAC/CEPAL
- IADB website
- ADB website
- IDS website
- BLDS website
- Social Science Research Network
- 3iE website

6. Classification of studies

Studies that have passed both screening stages will be classified and described in an annotated bibliography. The classification tables will include the following information:

- authors and year of study
- geographical coverage
- detailed description of intervention and context
- population
- methods, sampling and data
- findings on design and implementation factor
- contextual factors of importance Sub-question 2c: What is the effect of targeting on programme outcomes?

1. The review research questions

The systematic literature reviews should assess the state of knowledge on the following question: *What is known about the effect of targeting on cash transfer programme outcomes?*

2. Methodology

The systematic literature reviews should combine three tracks. These tracks are briefly explained here and further instructions are given below.

1. **Bibliographic database search:** Searching a previously agreed upon list of academic databases, using consistent search strings (see below) that have been tested beforehand and applying inclusion/exclusion criteria.

2. **Snowball technique:** Contacting approximately three key experts in the field and asking them for recommendations for important studies on the research question. This also includes looking at the experts’ websites and publication lists and including relevant studies. Finally, we will be looking for further relevant studies in the bibliographies of the experts’ studies and recommended studies.

3. **Websites searches:** Searching previously agreed on websites (see below) for relevant studies using similar search terms as for the bibliographic databases. This also includes a google search for other grey literature.

Studies will be screened and assessed using the EPPI Reviewer software. After an initial broad screening process that considers overall study design, as well as other broader inclusion/exclusion criteria, a second round of screening will be conducted. The second stage assessment will depend on the type of study. In the case of impact evaluation studies, the same assessment tool used for those studies retrieved in research question one will be applied. In the case of qualitative and descriptive studies and institutional analysis, an assessment of methodological rigour based on the literature around evaluating qualitative studies will be applied.

The relevant studies that make it through both stages of screening will be summarised in an annotated bibliography. The annotated bibliography lists the relevant studies in table format (see below) and briefly summarises each study in terms of relevant information on methodology, intervention and findings. More specifically, the relevant studies will also be summarised and classified in a table summarising the following information: i) publication details, (ii) description of the intervention and context, (iii) methods, data and sampling, (iv) population, v) findings of relevance to the research question including findings of statistically significant and non-significant impacts and disaggregation (e.g. by gender, age and other characteristics), and vi) contextual factors of importance.

A narrative synthesis approach will be applied to synthesise the findings. 3. Bibliographic database search

The research question

The research question is ‘What is known about the effect of targeting on cash transfer programme outcomes?’ Here we want to know how targeting mediates programme impacts.

In order to understand it better, the research question can be decomposed into population, intervention and design/implementation factor:

| Population | Intervention | Design/implementation factor | |------------|--------------|-----------------------------| | People living in low or middle income countries and who either receive the intervention or are the comparison group | Conditional or unconditional cash transfers | Targeting |

| Cash transfer | Social transfer | Financial transfer | Monetary transfer | Child grant/ disability grant/ old-age grant/ social grant | Social assistance | Social pension | Non-contributory pension | Old age pension | Child benefit/ disability benefit/ old-age benefit | Basic income/ minimum income | UCT/ CCT | Income support | |---------------|-----------------|--------------------|------------------|----------------------------------------------------------|-----------------|-----------------|------------------------|----------------|-----------------------------------------------|-----------------------------|----------|--------------| | Target\* | Geographical target\* | Categorical target\* | Poverty target\* | Community-based target\* | Targeting errors | Proxy-means test/ PMT | Means-test\* | Beneficiary identification | Beneficiary selection | Recertification | Target\* frequency | Inclusion error | Exclusion error | Undercoverage | Over selection | Under selection | Leakage | Incidence | Take-up |

The population has been restricted to people living in low and middle income countries. This includes both beneficiary and control households. The aim of the research question is to analyse the effect of targeting on cash transfers outcomes. The design/implementation factor for this sub-question is targeting. The table above also includes all synonyms that will be used in the searches.

Search strings

The search string will be composed of intervention (part 1), design and implementation factor (part 2) and country filter (example below given for SCOPUS filter). In order to capture all possible cash transfers, search strings should include all synonyms listed above. In terms of design/implementation factors, we will use targeting in the search strings. The following search strings and will be used (they have been tested in the pilot phase):

1. TITLE-ABS-KEY ( “Cash transfer\*” OR “social transfer\*” OR “financial transfer\*” OR “monetary transfer\*” OR “child grant\*” OR “disability grant\*” OR “old age grant\*” OR “social grant\*” OR “basic grant\*” OR “minimum income grant\*” OR “social assistance” OR welfare OR “social pension\*” OR “non-contributory pension\*” OR “old age pension\*” OR “child benefit\*” OR “disability benefit\*” OR “old age benefit\*” OR cct OR uct OR “income support” )

2. TITLE-ABS-KEY (targeted OR “geographical target\*” OR “categorical target\*” OR “poverty target\*” OR universal OR “community-based target\*” OR “CBT” OR “targeting error\*” OR “proxy means test\*” OR PMT OR “means-test\*” OR “beneficiary identification” OR beneficiary W/1 (identification OR selection) OR recertification OR targeting W/1 frequency OR “inclusion error\*” OR “exclusion error\*” OR “undercoverage” OR “leakage\*” OR “over selection” OR “under selection” OR incidence OR “take-up” ) Cash transfers: what does the evidence say?

3. (TITLE-ABS-KEY((afghanistan OR albania OR algeria OR angola OR argentina OR armenia OR armenian OR aruba OR azerbaijan OR bangladesh OR benin OR byelarus OR byelorussian OR belarus OR belorussian OR belorussia OR belize OR bhutan OR bolivia OR bosnia OR herzegovina OR hercegovina OR botswana OR brasil OR brazil OR bulgaria OR “Burkina Faso” OR “Burkina Fasso” OR “Upper Volta” OR burundi OR urundi OR cambodia OR “Khmer Republic” OR kampuchea OR cameroon OR cameroons OR cameror OR cameron OR camoros OR “Cape Verde” OR “Central African Republic” OR chad OR china OR colombia OR comoros OR “Comoro Islands” OR comores OR mayotte OR congo OR zaire OR “Costa Rica”” OR “Cote d’Ivoire” OR “Ivory Coast” OR cuba OR djibouti OR “French Somaliland” OR dominica OR “Dominican Republic” OR “East Timor” OR “East Timur” OR “Timor Leste” OR ecuador OR egypt OR “United Arab Republic” OR “El Salvador” OR eritrea OR ethiopia OR fiji OR gabon OR “Gabonese Republic” OR gambia OR gaza OR “Georgia Republic” OR “Georgian Republic” OR ghana OR grenada OR guatemala OR guinea OR guiana OR guyana OR haiti OR hungary OR honduras OR india OR iran OR iraq OR jamaica OR jordan OR kazakhstan OR kazakhstan OR keny OR kiribati OR korea OR kosovo OR kyrgyzstan OR kirghizia OR “Kyrgyz Republic” OR kirghiz OR kirgizstan OR “Lao PDR” OR laos OR lebanon OR lesotho OR basutoland OR liberia OR libya OR macedonia OR madagascar OR “Malagasy Republic” OR malaysia OR malaya OR malay OR sabah OR sarawak OR malawi OR mali OR “Marshall Islands” OR mauritania OR mauritius OR “Agalega Islands” OR mexico OR micronesia OR “Middle East” OR moldova OR moldovia OR moldovian OR mongolia OR montenegro OR morocco OR ifni OR mozambique OR myanmar OR myanmar OR burma OR namibia OR nepal OR “Netherlands Antilles” OR “New Caledonia” OR nicaragua OR niger OR niger OR pakistan OR palau OR palestine OR panama OR paraguay OR peru OR philippines OR philippines OR philippines OR “Puerto Rico” OR romania OR rumania OR rounmania OR rwanda OR ruanda OR “Saint Lucia” OR “St Lucia” OR “Saint Vincent” OR “St Vincent” OR grenadines OR samoan OR “Samoan Islands” OR “Navigator Island” OR “Navigator Islands” OR “Sao Tome” OR senegal OR serbia OR montenegro OR seychelles OR “Sierra Leone” OR “Sri Lanka” OR “Solomon Islands” OR somalia OR “South Africa” OR sudan OR suriname OR surinam OR swaziland OR syria OR tajikistan OR tadzhikistan OR tadzhikistan OR tanzania OR thailand OR togo OR togoles republic OR tonga OR tunisia OR turkey OR turkmenistan OR turkmen OR uganda OR ukraine OR uzbekistan OR uzbek OR vanuatu OR “New Hebrides” OR venezuela OR vietnam OR “Viet Nam” OR “West Bank” OR yemen OR yugoslavia OR zambia OR zimbabwe ) ) OR (TITLE-ABS-KEY(“Developing Countries” OR africa OR asia OR caribbean OR “West Indies” OR “South America” OR “Latin America” OR “Central America” OR ((developing OR “less\* developed” OR “under developed” OR underdeveloped OR “middle income” OR “low\* income” OR underserved OR “under served” OR deprived OR poor\*) W/1 ( countr\* OR nation\* OR population\* OR world ) ) ) OR (TITLE-ABS-KEY(((developing OR “less\* developed” OR “under developed” OR underdeveloped OR “middle income” OR “low\* income” ) W/1 ( economy OR economies ) ) OR (low\* W/1 ( gdp OR gnp OR “gross domestic” OR “gross national” ) ) OR (low W/3 middle W/3 countr\* ) ) ) OR (TITLE-ABS-KEY(((lmic OR lmic OR “third world” OR “lami countr\*” ) ) OR “transitional countr\*” ) ) TITLE-ABS-KEY(afghanistan OR albania OR algeria OR angola OR argentina OR armenia OR armenian OR aruba OR azerbaijan OR bangladesh OR benin OR byelarus OR byelorussian OR belarus OR belorussian OR belorussia OR belize OR bhutan OR bolivia OR bosnia OR hercegovina OR hercegovina OR botswana OR brasil OR brazil OR bulgaria OR “Burkina Faso” OR “Burkina Fasso” OR “Upper Volta” OR burundi OR urundi OR cambodia OR “Khmer Republic” OR kampuchea OR cameroon OR cameroons OR cameror OR cameron OR camoros OR “Cape Verde” OR “Central African Republic” OR chad OR china OR colombia OR comoros OR “Comoro Islands” OR comores OR mayotte OR congo OR zaire OR “Costa Rica”” OR “Cote d’Ivoire” OR “Ivory Coast” OR cuba OR djibouti OR “French Somaliland” OR dominica OR “Dominican Republic” OR “East Timor” OR “East Timur” OR “Timor Leste” OR ecuador OR egypt OR “United Arab Republic” OR “El Salvador” OR eritrea OR ethiopia OR fiji OR gabon OR “Gabonese Republic” OR gambia OR gaza OR “Georgia Republic” OR “Georgian Republic” OR ghana OR grenada OR guatemala OR guinea OR guiana OR guyana OR haiti OR hungary OR honduras OR india OR maldives OR indonesia OR iran OR iraq OR jamaica OR jordan OR kazakhstan OR kazakh OR kenya OR kiribati OR korea OR kosovo OR kyrgyzstan OR kirghizia OR “Kyrgyz Republic” OR kirghiz OR kirgizstan OR “Lao PDR” OR laos OR lebanon OR lesotho OR basutoland OR liberia OR libya OR macedonia OR madagascar OR “Malagasy Republic” OR malasia OR malaya OR malay OR sabah OR sarawak OR malawi OR mali OR “Marshall Islands” OR mauritania OR mauritius OR “Agalega Islands” OR mexico OR micronesia OR “Middle East” OR moldova OR moldovia OR moldovan OR mongolia OR montenegro OR morocco OR ifni OR mozambique OR myanmar OR myanmar OR burma OR namibia OR nepal OR “Netherlands Antilles” OR “New Caledonia” OR nicaragua OR niger OR nigeria OR pakistan OR palau OR palestine OR panama OR paraguay OR peru OR philippines OR philipines OR philipines OR philippines OR “Puerto Rico” OR romania OR rumania OR roumania OR rwanda OR ruanda OR “Saint Lucia” OR “St Lucia” OR “Saint Vincent” OR “St Vincent” OR grenadines OR samoa OR “Samoa Islands” OR “Navigator Island” OR “Navigator Islands” OR “Sao Tome” OR senegal OR serbia OR montenegro OR seychelles OR “Sierra Leone” OR “Sri Lanka” OR “Solomon Islands” OR somalia OR “South Africa” OR sudan OR suriname OR surinam OR swaziland OR syria OR tajikistan OR tadzhikistan OR tadzikistan OR tadzhik OR tanzania OR thailand OR togo OR togoles republic OR tonga OR tunisia OR turkey OR turkmenistan OR turkmen OR uganda OR ukraine OR uzbekistan OR uzbek OR vanuatu OR “New Hebrides” OR venezuela OR vietnam OR “Viet Nam” OR “West Bank” OR yemen OR yugoslavia OR zambia OR zimbabwe ) OR TITLE-ABS-KEY ( “Developing Countries” OR africa OR asia OR caribbean OR “West Indies” OR “South America” OR “Latin America” OR “Central America” OR developing OR “less\* developed” OR “under developed” OR underdeveloped OR “middle income” OR “low\* income” OR underserved OR “under served” OR deprived ) OR TITLE-ABS-KEY ( poor\* W/1 countr\* OR nation\* OR population\* OR world ) OR TITLE-ABS-KEY ( developing OR “less\* developed” OR “under developed” OR underdeveloped OR “middle income” OR “low\* income” ) W/1 econom\* ) OR TITLE-ABS-KEY ( low\* W/1 gdp OR gnp OR “gross domestic” OR “gross national” ) OR TITLE-ABS-KEY ( low W/3 middle W/3 countr\* ) OR TITLE-ABS-KEY ( lmic OR lmics OR “third world” OR “lami countr\*” OR “transitional countr\*” )

4. Search strings to run in Scopus: #1 AND #2 AND #3 (limited to 2000 onwards)

**Inclusion criteria**

**Stage 1 Screening:**

Inclusion criteria help in deciding whether a study that has been found is relevant. The following inclusion criteria will be applied during the first stage of the screening process (all criteria need to be satisfied for the study to be included). They will be applied to titles, then abstracts, then full text. All studies that are included on the basis of the first stage screening process, will be included in the Stage 2 screening process.

1. **Date:** From 2000
2. **Language:** The review is restricted to English studies
3. **Population:** People that have received a cash transfer, or control households
4. **Geographical locations:** Low and middle income countries
5. **Interventions:** Conditional or unconditional cash transfers. The programmes should be non-contributory, publicly mandated or NGO-provided (so not private transfers, like remittances, or religious donations).
6. **Study design:** The study should be an empirical study (i.e. based on data and or fieldwork) or an institutional analysis. It can be qualitative or quantitative. [Not theoretical; no literature review; not descriptive]
7. **Design/ implementation factor:** targeting
8. **Analysis:** Design and implementation factors are explicitly linked to outcomes. Stage 2 Screening:

The second stage assessment will depend on the type of study. In the case of impact evaluation studies, the same assessment tool used for those studies retrieved in research question one will be applied. In the case of qualitative and descriptive studies and institutional analysis, an assessment of methodological rigour based on the literature around evaluating qualitative studies will be applied.

List of databases used

- SCOPUS (Elsevier). This database includes 5,682 journals, conference proceedings, trade publications and book series in the Social Sciences category.
- IDEAS-Repec

4. Snowball technique

The following three people should be contacted and asked for the five most relevant studies on the research question. We will also look at their websites for relevant publications.

1. Emmanuel Skoufias, World Bank
2. David Coady, IMF
3. Franziska Gassmann, Maastricht University

Studies shared by experts will be assessed against Stage 1 and Stage 2 screening criteria. We will also check the reference lists of the studies obtained for any further studies that fit the inclusion criteria.

5. Websites searches

The following websites/search engines should be consulted, if possible using the same search strings as for the academic databases. Any studies found on these websites will be assessed against the same Stage 1 and Stage 2 screening criteria.

- Google Scholar (the first five pages)
- World Bank
- R4D DFID
- International Policy Centre for Inclusive Growth (IPC-IG)
- International Food Policy Research Institute (IFPRI)
- GSDRC
- Transfer Project (UNC Chapel Hill)
- ECLAC/CEPAL
- IADB website
- ADB website
- IDS website
- BLDS website
- Social Science Research Network
- 3iE website

6. Classification of studies

Studies that have passed both screening stages will be classified and described in an annotated bibliography. The classification tables will include the following information:

- authors and year of study
- geographical coverage
- detailed description of intervention and context
- population
- methods, sampling and data
- summary findings on design and implementation factor Sub-question 2d: What is the effect of payment systems on cash transfer programme outcomes?

1. The review research questions

The systematic literature reviews should assess the state of knowledge on the following question: *What is known about the effect of payment systems on cash transfer programme outcomes?*

2. Methodology

The systematic literature reviews should combine three tracks. These tracks are briefly explained here and further instructions are given below.

1. **Bibliographic database search:** Searching a previously agreed upon list of academic databases, using consistent search strings (see below) that have been tested beforehand and applying inclusion/exclusion criteria.

2. **Snowball technique:** Contacting approximately four key experts in the field and asking them for recommendations for important studies on the research question. This also includes looking at the experts’ websites and publication lists and including relevant studies. Finally, we will be looking for further relevant studies in the bibliographies of the experts’ studies and recommended studies.

3. **Websites searches:** Searching previously agreed on websites (see below) for relevant studies using similar search terms as for the bibliographic databases. This also includes a google search for other grey literature.

Studies will be screened and assessed using the EPPI Reviewer software. After an initial broad screening process that considers overall study design, as well as other broader inclusion/exclusion criteria, a second round of screening will be conducted. The second stage assessment will depend on the type of study. In the case of impact evaluation studies, the same assessment tool used for those studies retrieved in research question one will be applied. In the case of qualitative and descriptive studies and institutional analysis, an assessment of methodological rigour based on the literature around evaluating qualitative studies will be applied.

The relevant studies that make it through both stages of screening will be summarised in an annotated bibliography. The annotated bibliography lists the relevant studies in table format (see below) and briefly summarises each study in terms of relevant information on methodology, intervention and findings. More specifically, the relevant studies will also be summarised and classified in a table summarising the following information: i) publication details, (ii) description of the intervention and context, (iii) methods, data and sampling, (iv) population, (v) findings of relevance to the research question including findings of statistically significant and non-significant impacts and disaggregation (e.g. by gender, age and other characteristics), and (vi) contextual factors of importance.

A narrative synthesis approach will be applied to synthesise the findings. 3. Bibliographic database search

The research question

The research question is ‘What is known about the effect of payment systems on programme outcomes?’ Here we want to know how payment frequency in practice, mode of payment and any irregularities in the payment process mediate programme impacts.

In order to understand it better, the research question can be decomposed into population, intervention and design/implementation factor:

| Population | Intervention | Design/ implementation factor | |------------|--------------|------------------------------| | People living in low or middle income countries and who either receive the intervention or are the comparison group | Conditional or unconditional cash transfers | Payment systems | | Cash transfer | Payment | Regular | | Social transfer | Regular | Irregular | | Financial transfer | Predictable\* | Reliability\* | | Monetary transfer | Frequency | One-off | | Child grant/ disability grant/ old-age grant/ social grant | Delay\* | Lump | | Social assistance | Late | Bank | | Social pension | Basic income/ minimum income | Mobile transfer | | Non-contributory pension | UCT/ CCT | MT0 | | Old age pension | Income support | Post office | | Child benefit/ disability benefit/ old-age benefit | ATM | Smart card | | Basic income/ minimum income | Bank | Electronic card\* | | UCT/ CCT | Late | Biometric card\* | | Income support | Bank | Bribe | | | | Rent | | | | Corruption | | | | Fraud | | | | Cash | | | | Savings and Credit Cooperative (SACCO) | | | | Microfinance institution |

The population has been restricted to people living in low and middle income countries. This includes both beneficiary and control households. The aim of the research question is to analyse the effect of the payment system on cash transfers outcomes. The design/implementation factors for this sub-question are payment frequency in practice, mode of payment and any irregularities in the payment process. The table above also includes all synonyms that will be used in the searches.

Search strings

The search string will be composed of intervention (part 1), design and implementation factor (part 2) and country filter (example below given for SCOPUS filter). In order to capture all possible cash transfers, search strings should include all synonyms listed above. In terms of design/implementation factors, we will use payment frequency in practice, mode of payment and any irregularities in the payment process and synonyms in the search strings. The following search strings will be used (they have been tested in the pilot phase):

1. TITLE-ABS-KEY ( “Cash transfer” OR “social transfer” OR “financial transfer” OR “monetary transfer” OR “child grant” OR “disability grant” OR “old age grant” OR “social grant” OR “basic grant” OR “minimum income grant” OR “social assistance” OR welfare OR “social pension” OR “non-contributory pension” OR “old age pension” OR “child benefit” OR “disability benefit” OR “old age benefit” OR “cct” OR “uct” OR “income support” )

2. TITLE-ABS-KEY (delivery OR payment\* OR regular\* OR irregular\* OR lump\* OR frequency OR one-off OR delay\* OR predict\* OR reliab\* OR ATM OR late OR bank OR “mobile transfer\*” OR MTO OR “post office\*” OR “smart card\*” OR “electronic card\*” OR “biometric card\*” OR bribe\* OR rent OR corruption)

3. TITLE-ABS-KEY (afghanistan OR albania OR algeria OR angola OR argentina OR armenia OR armenian OR aruba OR azerbaijan OR bangladesh OR benin OR byelarus OR byelorussian OR belarus OR belorussian OR belorussia OR belize OR bhutan OR bolivia OR bosnia OR herzegovina OR hercegovina OR botswana OR brasil OR brazil OR bulgaria OR “Burkina Faso” OR “Burkina Fasso” OR “Upper Volta” OR burundi OR urundi OR cambodia OR “Khmer Republic” OR kampuchea OR cameroon OR cameroons OR cameron OR camorons OR “Cape Verde” OR “Central African Republic” OR chad OR china OR colombia OR comoros OR “Comoro Islands” OR comores OR mayotte OR congo OR zaire OR “Costa Rica” OR “Cote d’Ivoire” OR “Ivory Coast” OR cuba OR djibouti OR “French Somaliland” OR dominica OR “Dominican Republic” OR “East Timor” OR “East Timur” OR “Timor Leste” OR ecuador OR egypt OR “United Arab Republic” OR “El Salvador” OR eritrea OR ethiopia OR fiji OR gabon OR “Gabonese Republic” OR gambia OR gaza OR “Georgia Republic” OR “Georgian Republic” OR ghana OR grenada OR guatemala OR guinea OR guiana OR guyana OR haiti OR hungary OR honduras OR india OR maldives OR indonesia OR iran OR iraq OR jordan OR kazakhstan OR kazakh OR kenya OR kiribati OR korea OR kosovo OR krygyzstan OR kirghizia OR “Kyrgyz Republic” OR kirghiz OR kirgizstan OR “Lao PDR” OR laos OR lebanon OR lesotho OR basutoland OR liberia OR libya OR macedonia OR madagascar OR “Malagasy Republic” OR malaysia OR malay OR malay OR sahab OR sarawak OR malawi OR mali OR “Marshall Islands” OR mauritania OR mauritius OR “Agalega Islands” OR mexico OR micronesia OR “Middle East” OR moldova OR moldavia OR moldovan OR mongolia OR montenegro OR morocco OR ifni OR mozambique OR myanmar OR myanmar OR burma OR namibia OR nepal OR “Netherlands Antilles” OR “New Caledonia” OR nicaragua OR niger OR nigeria OR pakistan OR palau OR palestine OR panama OR paraguay OR peru OR philippines OR philippines OR philippines OR “Puerto Ric\*” OR romania OR rumania OR roumania OR rwanda OR ruanda OR “Saint Lucia” OR “St Lucia” OR “Saint Vincent” OR “St Vincent” OR grenadines OR samoan OR “Samoan Islands” OR “Navigator Island” OR “Navigator Islands” OR “Sao Tome” OR “Sao Tome” OR senegal OR serbia OR montenegro OR seychelles OR “Sierra Leone” OR “Sri Lanka” OR “Solomon Islands” OR somalia OR “South Africa” OR sudan OR suriname OR surinam OR swaziland OR syria OR tajikistan OR tajikistan OR tadjikistan OR tadjik OR tanzania OR thailand OR togo OR togoles republic OR tonga OR tunisia OR turkey OR turkmenistan OR turkmen OR uganda OR ukraine OR uzbekistan OR uzbek OR vanuatu OR “New Hebrides” OR venezuela OR vietnam OR “Viet Nam” OR “West Bank” OR yemen OR yugoslavia OR zambia OR zimbabwe ) OR TITLE-ABS-KEY ( “Developing Countries” OR africa OR asia OR caribbean OR “West Indies” OR “South America” OR “Latin America” OR “Central America” OR developing OR “less\* developed” OR “under developed” OR underdeveloped OR “middle income” OR “low\* income” OR underserved OR “under served” OR deprived ) OR TITLE-ABS-KEY (poor\* W/1 countr\* OR nation\* OR population\* OR world ) OR TITLE-ABS-KEY ( developing OR “less\* developed” OR “under developed” OR underdeveloped OR “middle income” OR “low\* income” ) W/1 econom\* ) OR TITLE-ABS-KEY ( low\* W/1 gdp OR gnp OR “gross domestic” OR “gross national” ) OR TITLE-ABS-KEY (low W/3 middle W/3 countr\* ) OR TITLE-ABS-KEY ( lmic OR lmc OR “third world” OR “lami countr\*” OR “transition countr\*” )

4. Search strings to run in Scopus: #1 AND #2 AND #3 (limited to 2000 onwards) Inclusion criteria

Stage 1 Screening:

Inclusion criteria help in deciding whether a study that has been found is relevant. The following inclusion criteria will be applied during the first stage of the screening process (all criteria need to be satisfied for the study to be included). They will be applied to titles, then abstracts, then full text. All studies that are included on the basis of the first stage screening process, will be included in the Stage 2 screening process.

1. Date: From 2000
2. Language: The review is restricted to English studies
3. Population: People that have received a cash transfer, or control households
4. Geographical locations: Low and middle income countries
5. Interventions: Conditional or unconditional cash transfers. The programmes should be non-contributory, publicly mandated or NGO-provided (so not private transfers, like remittances, or religious donations)
6. Study design: The study should be an empirical study (i.e. based on data and or fieldwork) or an institutional analysis. It can be qualitative or quantitative. [Not theoretical; no literature review; not descriptive]
7. Design/implementation factor: payment frequency in practice, mode of payment and any irregularities in the payment process
8. Analysis: Design and implementation factors are explicitly linked to outcomes

Stage 2 Screening:

The second stage assessment will depend on the type of study. In the case of impact evaluation studies, the same assessment tool used for those studies retrieved in research question one will be applied. In the case of qualitative and descriptive studies and institutional analysis, an assessment of methodological rigour based on the literature around evaluating qualitative studies will be applied.

List of databases used

- SCOPUS (Elsevier). This database includes 5,682 journals, conference proceedings, trade publications and book series in the Social Sciences category.
- IDEAS-Repec

4. Snowball technique

The following four people should be contacted and asked for the five most relevant studies on the research question. We will also look at their websites for relevant publications.

1. Clare O’Brien, OPM
2. Alan Gelb, Centre for Global Development
3. Stephen Devereux, IDS
4. Gabriele Smith, Development Pathways

Studies shared by experts will be assessed against Stage 1 and Stage 2 screening criteria. We will also check the reference lists of the studies obtained for any further studies that fit the inclusion criteria. 5. Websites searches

The following websites/search engines should be consulted, if possible using the same search strings as for the academic databases. Any studies found on these websites will be assessed against the same Stage 1 and Stage 2 screening criteria.

- Google (the first five pages)
- World Bank
- R4D DFID
- International Policy Centre for Inclusive Growth (IPC-IG)
- International Food Policy Research Institute (IFPRI)
- GSDRC
- OPM website
- Transfer Project (UNC Chapel Hill)
- ECLAC/CEPAL
- IADB website
- ADB website
- IDS website
- BLDS website
- Social Science Research Network

6. Classification of studies

Studies that have passed both screening stages will be classified and described in an annotated bibliography. The classification tables will include the following information:

- authors and year of study
- geographical coverage
- detailed description of intervention and context
- population
- methods, sampling and data
- summary findings on design and implementation factor Sub-question 2e: What is the effect of grievance mechanisms and programme governance on programme outcomes?

1. The review research questions

The systematic literature reviews should assess the state of knowledge on the following question: *What is known about the effect of grievance mechanisms on programme outcomes?*

2. Methodology

The systematic literature reviews should combine three tracks. These tracks are briefly explained here and further instructions are given below.

1. **Bibliographic database search:** Searching a previously agreed upon list of academic databases, using consistent search strings (see below) that have been tested beforehand and applying inclusion/exclusion criteria.

2. **Snowball technique:** Contacting approximately three key experts in the field and asking them for recommendations for important studies on the research question. This also includes looking at the experts’ websites and publication lists and including relevant studies. Finally, we will be looking for further relevant studies in the bibliographies of the experts’ studies and recommended studies.

3. **Websites searches:** Searching previously agreed on websites (see below) for relevant studies using similar search terms as for the bibliographic databases. This also includes a google search for other grey literature.

Studies will be screened and assessed using the EPPI Reviewer software. After an initial broad screening process that considers overall study design, as well as other broader inclusion/exclusion criteria, a second round of screening will be conducted. The second stage assessment will depend on the type of study. In the case of impact evaluation studies, the same assessment tool used for those studies retrieved in research question one will be applied. In the case of qualitative and descriptive studies and institutional analysis, an assessment of methodological rigour based on the literature around evaluating qualitative studies will be applied.

The relevant studies that make it through both stages of screening will be summarised in an annotated bibliography. The annotated bibliography lists the relevant studies in table format (see below) and briefly summarises each study in terms of relevant information on methodology, intervention and findings. More specifically, the relevant studies will also be summarised and classified in a table summarising the following information: i) publication details, (ii) description of the intervention and context, (iii) methods, data and sampling, (iv) population, v) findings of relevance to the research question including findings of statistically significant and non-significant impacts and disaggregation (e.g. by gender, age and other characteristics), and vi) contextual factors of importance.

A narrative synthesis approach will be applied to synthesise the findings. 3. Bibliographic database search

The research question

The research question is ‘What is known about the effect of grievance mechanisms on programme outcomes?’ Here we want to know how design of grievance mechanisms mediate programme impacts.

In order to understand it better, the research question can be decomposed into population, intervention and design/implementation factor:

| Population | Intervention | Design/implementation factor | |------------|--------------|------------------------------| | People living in low or middle income countries and who either receive the intervention or are the comparison group | Conditional or unconditional cash transfers | Grievance mechanisms |

Cash transfer Social transfer Financial transfer Monetary transfer Child grant/ disability grant/ old-age grant/ social grant Social assistance Social pension Non-contributory pension Old age pension Child benefit/ disability benefit/ old-age benefit Basic income/ minimum income UCT / CDT Income support

Grievance Complaint Appeal Committee Resolution Redressal Social audit Community meeting Community monitoring Spot checks Feedback

The population has been restricted to people living in low and middle income countries. This includes both beneficiary and control households. The aim of the research question is to analyse the effect of the grievance mechanisms on cash transfers outcomes. The design/implementation factor for this sub-question is grievance mechanisms. The table above also includes all synonyms that will be used in the searches.

Search strings

The search string will be composed of intervention (part 1), design and implementation factor (part 2) and country filter (example below given for SCOPUS filter). In order to capture all possible cash transfers, search strings should include all synonyms listed above. In terms of design/implementation factors, we will use grievance mechanisms and synonyms in the search strings.

The following search strings and will be used (they have been tested in the pilot phase):

1. TITLE-ABS-KEY ( “Cash transfer\*” OR “social transfer\*” OR “financial transfer\*” OR “monetary transfer\*” OR “child grant\*” OR “disability grant\*” OR “old age grant\*” OR “social grant\*” OR “basic grant\*” OR “minimum income grant\*” OR “social assistance” OR welfare OR “social pension\*” OR “non-contributory pension\*” OR “old age pension\*” OR “child benefit\*” OR “disability benefit\*” OR “old age benefit\*” OR cct OR uct OR “income support” )

2. TITLE-ABS-KEY (Grievance\* OR Complaint\* OR Appeal\* OR Committee\* OR Resol\* OR Redress\* OR “Social audit\*” OR “Community meeting\*” OR “Community monitoring” OR “Spot check\*” OR “Feedback”)

3. TITLE-ABS-KEY ( afghanistan OR albania OR algeria OR angola OR argentina OR armenia OR armenian OR aruba OR azerbaijan OR bangladesh OR benin OR byelarus OR byelorussian OR belarus OR belorussian OR belorussia OR belize OR bhutan OR bolivia OR bosnia OR herzegovina OR hercegovina OR botswana OR brasil OR brazil OR bulgaria OR “Burkina Faso” OR “Burkina Fasso” OR “Upper Volta” OR burundi OR urundi OR cambodia OR “Khmer Republic” OR kampuchea OR cameroon OR cameroons OR camer OR cameron OR camoros OR “Cape Verde” OR “Central African Republic” OR chad OR china OR colombia OR comoros OR “Comoro Islands” OR comores OR... mayotte OR congo OR zaire OR “Costa Rica?” OR “Cote d’Ivoire” OR “Ivory Coast” OR cuba OR djibouti OR “French Somaliland” OR dominica OR “Dominican Republic” OR “East Timor” OR “East Timur” OR “Timor Leste” OR ecuador OR egypt OR “United Arab Republic” OR “El Salvador” OR eritrea OR ethiopia OR fiji OR gabon OR “Gabonese Republic” OR gambia OR gaza OR “Georgia Republic” OR “Georgian Republic” OR ghana OR grenada OR guatemala OR guinea OR guiana OR guyana OR haiti OR hungary OR honduras OR india OR maldives OR indonesia OR iran OR iraq OR jamaica OR jordan OR kazakhstan OR kazakh OR kenya OR kiribati OR korea OR kosovo OR kyrgyzstan OR kirghizia OR “Kyrgyz Republic” OR kirghiz OR kirgizstan OR “Lao PDR” OR laos OR lebanon OR lesotho OR basutoland OR liberia OR libya OR macedonia OR madagascar OR “Malagasy Republic” OR malaysia OR malaya OR malay OR malay OR malay OR malawi OR mali OR “Marshall Islands” OR mauritania OR mauritius OR “Agalega Islands” OR mexico OR micronesia OR “Middle East” OR moldova OR moldovia OR mongolia OR montenegro OR morocco OR ifni OR mozambique OR myanmar OR myanmar OR burma OR namibia OR nepal OR “Netherlands Antilles” OR “New Caledonia” OR nicaragua OR niger OR nigeria OR pakistan OR palau OR palestine OR panama OR paraguay OR peru OR philippines OR philippines OR philippines OR philippines OR “Puerto Rico” OR romania OR rumania OR roumania OR rwanda OR ruanda OR “Saint Lucia” OR “St Lucia” OR “Saint Vincent” OR “St Vincent” OR grenadines OR samoa OR “Samoa Islands” OR “Navigator Island” OR “Navigator Islands” OR “Sao Tome” OR senegal OR serbia OR montenegro OR seychelles OR “Sierra Leone” OR “Sri Lanka” OR “Solomon Islands” OR somalia OR “South Africa” OR sudan OR suriname OR surinam OR swaziland OR syria OR tajikistan OR tadzhikistan OR tadzhi OR tanzania OR thailand OR togo OR togolese republic OR tonga OR tunisia OR turkey OR turkmenistan OR turkmen OR uganda OR ukraine OR uzbekistan OR uzbek OR vanuatu OR “New Hebrides” OR venezuela OR vietnam OR “Viet Nam” OR “West Bank” OR yemen OR yugoslavia OR zambia OR zimbabwe OR TITTLE-ABS-KEY (“Developing Countries” OR africa OR asia OR caribbean OR “West Indies” OR “South America” OR “Latin America” OR “Central America” OR developing OR “less\* developed” OR “under developed” OR underdeveloped OR “middle income” OR “low\* income” OR underserved OR “under served” OR deprived) OR TITTLE-ABS-KEY (poor\* W/1 countr\* OR nation\* OR population\* OR world ) OR TITTLE-ABS-KEY ( developing OR “less\* developed” OR “under developed” OR underdeveloped OR “middle income” OR “low\* income” ) W/1 econom\* ) OR TITTLE-ABS-KEY ( low\* W/1 gdp OR gnp OR “gross domestic” OR “gross national” ) OR TITTLE-ABS-KEY (low W/3 middle W/3 countr\* ) OR TITTLE-ABS-KEY ( lmic OR lmics OR “third world” OR “lami countr\*” OR “transitional countr\*” )

4. Search strings to run in Scopus: #1 AND #2 AND #3 (limited to 2000 onwards)

**Inclusion criteria**

**Stage 1 Screening:**

Inclusion criteria help in deciding whether a study that has been found is relevant. The following inclusion criteria will be applied during the first stage of the screening process (all criteria need to be satisfied for the study to be included). They will be applied to titles, then abstracts, then full text. All studies that are included on the basis of the first stage screening process, will be included in the Stage 2 screening process.

1. **Date:** From 2000

2. **Language:** The review is restricted to English studies

3. **Population:** People that have received a cash transfer, or control households

4. **Geographical locations:** Low and middle income countries

5. **Interventions:** Conditional or unconditional cash transfers. The programmes should be non-contributory, publicly mandated or NGO-provided (so not private transfers, like remittances, or religious donations).

6. **Study design**: The study should be an empirical study (i.e. based on data and or fieldwork) or an institutional analysis. It can be qualitative or quantitative. [Not theoretical; no literature review; not descriptive]

7. **Design/ implementation factor**: grievance mechanisms

8. **Analysis**: Design and implementation factors are explicitly linked to outcomes.

**Stage 2 Screening:**

The second stage assessment will depend on the type of study. In the case of impact evaluation studies, the same assessment tool used for those studies retrieved in research question one will be applied. In the case of qualitative and descriptive studies and institutional analysis, an assessment of methodological rigour based on the literature around evaluating qualitative studies will be applied.

**List of databases used**

- SCOPUS (Elsevier). This database includes 5,682 journals, conference proceedings, trade publications and book series in the Social Sciences category.
- IDEAS-Repec

**4. Snowball technique**

The following four people should be contacted and asked for the five most relevant studies on the research question. We will also look at their websites for relevant publications.

1. Valentina Barca, OPM
2. Nicola Jones, ODI
3. Francisco Ayala, Ayala Consulting
4. Sam Hickey, University of Manchester

Studies shared by experts will be assessed against Stage 1 and Stage 2 screening criteria. We will also check the reference lists of the studies obtained for any further studies that fit the inclusion criteria.

**5. Websites searches**

The following websites/ search engines should be consulted, if possible using the same search strings as for the academic databases. Any studies found on these websites will be assessed against the same Stage 1 and Stage 2 screening criteria.

- Google (the first five pages)
- World Bank
- R4D DFID
- International Policy Centre for Inclusive Growth (IPC-IG)
- International Food Policy Research Institute (IFPRI)
- GSDRC
- OPM website
- Transfer Project (UNC Chapel Hill)
- ECLAC/ CEPAL
- IADB website
- ADB website
- IDS website
- BLDS website
- Social Science Research Network

6. Classification of studies

Studies that have passed both screening stages will be classified and described in an annotated bibliography. The classification tables will include the following information:

- authors and year of study
- geographical coverage
- detailed description of intervention and context
- population
- methods, sampling and data
- summary findings on design and implementation factor Sub-question 2f: What is the effect of complementary and supply-side services on programme outcomes?

1. The review research questions

The systematic literature reviews should assess the state of knowledge on the following question: *What is known about the effect of complementary services on programme outcomes?*

2. Methodology

The systematic literature reviews should combine three tracks. These tracks are briefly explained here and further instructions are given below.

1. **Bibliographic database search:** Searching a previously agreed upon list of academic databases, using consistent search strings (see below) that have been tested beforehand and applying inclusion/exclusion criteria.

2. **Snowball technique:** Contacting approximately five key experts in the field and asking them for recommendations for important studies on the research question. This also includes looking at the experts’ websites and publication lists and including relevant studies. Finally, we will be looking for further relevant studies in the bibliographies of the experts’ studies and recommended studies.

3. **Websites searches:** Searching previously agreed on websites (see below) for relevant studies using similar search terms as for the bibliographic databases. This also includes a google search for other grey literature.

Studies will be screened and assessed using the EPPI Reviewer software. After an initial broad screening process that considers overall study design, as well as other broader inclusion/exclusion criteria, a second round of screening will be conducted. The second stage assessment will depend on the type of study. In the case of impact evaluation studies, the same assessment tool used for those studies retrieved in research question one will be applied. In the case of qualitative and descriptive studies and institutional analysis, an assessment of methodological rigour based on the literature around evaluating qualitative studies will be applied.

The relevant studies that make it through both stages of screening will be summarised in an annotated bibliography. The annotated bibliography lists the relevant studies in table format (see below) and briefly summarises each study in terms of relevant information on methodology, intervention and findings. More specifically, the relevant studies will also be summarised and classified in a table summarising the following information: i) publication details, (ii) description of the intervention and context, (iii) methods, data and sampling, (iv) population, v) findings of relevance to the research question including findings of statistically significant and non-significant impacts and disaggregation (e.g. by gender, age and other characteristics), and vi) contextual factors of importance.

A narrative synthesis approach will be applied to synthesise the findings. 3. Bibliographic database search

The research question

The research question is ‘What is known about the effect of complementary services on programme outcomes?’ Here we want to know how complementary services mediate programme impacts.

In order to understand it better, the research question can be decomposed into population, intervention and design/implementation factor:

| Population | Intervention | Design/implementation factor | |------------|--------------|-----------------------------| | People living in low or middle income countries and who either receive the intervention or are the comparison group | Conditional or unconditional cash transfers | Complementary services |

| Cash transfer | Social transfer | Financial transfer | Monetary transfer | Child grant/ disability grant/ old-age grant/ social grant | Social assistance | Social pension | Non-contributory pension | Old age pension | Child benefit/ disability benefit/ old-age benefit | Basic income/ minimum income | UCT/ CCT | Complementary services | Accompanying services | Training | Campaign | Supply-side | Job search | Job matching | Income-generating opportunity\* | Livelihoods support | Financial services | Financial literacy | Microcredit | Skills training | Social work | Social care | Nutrition services | Sensitisation | Information campaign | Information meeting | Linkage\* | Case management | Social service | Social support | Child care | Parenting class | Legal aid | One stop shop | Coaching | Housing |

The population has been restricted to people living in low and middle income countries. This includes both beneficiary and control households. The aim of the research question is to analyse the effect of complementary services on cash transfers outcomes. The design/implementation factor for this sub-question is complementary services. The table above also includes all synonyms that will be used in the searches.

Search strings

The search string will be composed of intervention (part 1), design and implementation factor (part 2) and country filter (example below given for SCOPUS filter). In order to capture all possible cash transfers, search strings should include all synonyms listed above. In terms of design/implementation factors, we will complementary services and synonyms in the search strings. The following search strings and will be used (they have been tested in the pilot phase):

1. TITLE-ABS-KEY ( “Cash transfer\*” OR “social transfer\*” OR “financial transfer\*” OR “monetary transfer\*” OR “child grant\*” OR “disability grant\*” OR “old age grant\*” OR “social grant\*” OR “basic grant\*” OR “minimum income grant\*” OR “social assistance” OR welfare OR “social pension\*” OR “non-contributory pension\*” OR “old age pension\*” OR “child benefit\*” OR “disability benefit\*” OR “old age benefit\*” OR cct OR uct OR “income support” )

2. TITLE-ABS-KEY (“complementary service\*” OR training\* OR “accompanying service\*” OR campaign\* OR supply-side OR “job search\*” OR “job match\*” OR “income-generating opportunit\*” OR “livelihood” W/1 support\* OR “financial service\*” OR “financial literacy” OR microcredit\* OR microfinance OR “skill\*” training\*” OR “social work” OR “social care” OR “social service\*” OR “social support” OR “nutrition service\*” OR “sensitisation” OR sensitization OR “information campaign\*” OR “information meeting\*” OR “case management” OR linkage\* OR housing OR “child care” OR “parenting class\*” OR “legal aid” OR “one stop shop” OR coach\*)

3. TITLE-ABS-KEY (afghanistan OR albania OR algeria OR angola OR argentina OR armenia OR armenian OR aruba OR azerbaijan OR bangladesh OR benin OR byelarus OR byelorussian OR belarus OR belorussian OR belorussia OR belize OR bhutan OR bolivia OR bosnia OR herzegovina OR hercegovina OR botswana OR brasil OR brazil OR bulgaria OR “Burkina Faso” OR “Burkina Fasso” OR “Upper Volta” OR burundi OR urundi OR cambodia OR “Khmer Republic” OR kampuchea OR cameroon OR cameroons OR cameron OR camoros OR “Cape Verde” OR “Central African Republic” OR chad OR china OR colombia OR comoros OR “Comoro Islands” OR comores OR mayotte OR congo OR zaire OR “Costa Rica\*” OR “Cote d’Ivoire” OR “Ivory Coast” OR cuba OR djibouti OR “French Somaliland” OR dominica OR “Dominican Republic” OR “East Timor” OR “East Timur” OR “Timor Leste” OR ecuador OR egypt OR “United Arab Republic” OR “El Salvador” OR eritrea OR ethiopia OR fiji OR gabon OR “Gabonese Republic” OR gambia OR gaza OR “Georgia Republic” OR “Georgian Republic” OR ghana OR grenada OR guatemala OR guinea OR guiana OR guyana OR haiti OR hungary OR honduras OR india OR maldives OR indonesie OR iran OR iraq OR jamaica OR jordan OR kazakhstan OR kazakh OR kenya OR kiribati OR korea OR kosovo OR krygyzstan OR kirghizia OR “Krygz Republic” OR kirghiz OR kirgizstan OR “Lao PDR” OR laos OR lebanon OR lesotho OR basutoland OR liberia OR libya OR macedonia OR madagascar OR “Malagasy Republic” OR malaysia OR malaya OR malay OR sabah OR sarawak OR malawi OR mali OR “Marshall Islands” OR mauritania OR mauritius OR “Agalega Islands” OR mexico OR micronesia OR “Middle East” OR moldova OR moldovia OR moldovan OR mongolia OR montenegro OR morocco OR ifni OR mozambique OR myanmar OR myanmar OR burma OR namibia OR nepal OR “Netherlands Antilles” OR “New Caledonia” OR nicaragua OR niger OR nigeria OR pakistan OR palau OR palestine OR panama OR paraguay OR peru OR philippines OR philippines OR philippines OR “Puerto Ric\*” OR romania OR rumania OR roumania OR rwanda OR ruanda OR “Saint Lucia” OR “St Lucia” OR “Saint Vincent” OR “St Vincent” OR grenadines OR samoa OR “Samoa Islands” OR “Navigator Island” OR “Navigator Islands” OR “Sao Tome” OR senegal OR serbia OR montenegro OR seychelles OR “Sierra Leone” OR “Sri Lanka” OR “Solomon Islands” OR somalia OR “South Africa” OR sudan OR suriname OR surinam OR swaziland OR syria OR tajikistan OR tadzhikistan OR tadjikistan OR tadzhik OR tanzania OR thailand OR togo OR togoles republic OR tonga OR tunisia OR turkey OR turkmenistan OR turkmen OR uganda OR ukraine OR uzbekistan OR uzbek OR vanuatu OR “New Hebrides” OR venezuela OR vietnam OR “Viet Nam” OR “West Bank” OR yemen OR yugoslavia OR zambia OR zimbabwe) OR TITLE-ABS-KEY (“Developing Countries” OR africa OR asia OR caribbean OR “West Indies” OR “South America” OR “Latin America” OR “Central America” OR developing OR “less\*” developed OR “under developed” OR underdeveloped OR “middle income” OR “low\*” income OR underserved OR “under served” OR deprived) OR TITLE-ABS-KEY (poor\* W/1 countr\* OR nation\* OR population\* OR world) OR TITLE-ABS-KEY ((developing OR “less\*” developed) OR “under developed” OR underdeveloped OR “middle income” OR “low\*” income) W/1 econom\*)) OR TITLE-ABS-KEY (low\* W/1 gdp OR gnp OR “gross domestic” OR “gross national”) OR TITLE-ABS-KEY (low W/3 middle W/3 countr\*) OR TITLE-ABS-KEY (lmic OR lmic OR “third world” OR “lami countr\*” OR “transitional countr\*”)

4. Search strings to run in Scopus: #1 AND #2 AND #3 (limited to 2000 onwards) Inclusion criteria

Stage 1 Screening:

Inclusion criteria help in deciding whether a study that has been found is relevant. The following inclusion criteria will be applied during the first stage of the screening process (all criteria need to be satisfied for the study to be included). They will be applied to titles, then abstracts, then full text. All studies that are included on the basis of the first stage screening process, will be included in the Stage 2 screening process.

1. Date: From 2000
2. Language: The review is restricted to English studies
3. Population: People that have received a cash transfer, or control households
4. Geographical locations: Low and middle income countries
5. Interventions: Conditional or unconditional cash transfers. The programmes should be non-contributory, publicly mandated or NGO-provided (so not private transfers, like remittances, or religious donations).
6. Study design: The study should be an empirical study (i.e. based on data and or fieldwork) or an institutional analysis. It can be qualitative or quantitative. [Not theoretical; no literature review; not descriptive]
7. Design/ implementation factor: Complementary services
8. Analysis: Design and implementation factors are explicitly linked to outcomes.

Stage 2 Screening:

The second stage assessment will depend on the type of study. In the case of impact evaluation studies, the same assessment tool used for those studies retrieved in research question one will be applied. In the case of qualitative and descriptive studies and institutional analysis, an assessment of methodological rigour based on the literature around evaluating qualitative studies will be applied.

List of databases used

- SCOPUS (Elsevier). This database includes 5,682 journals, conference proceedings, trade publications and book series in the Social Sciences category.
- IDEAS-Repec

4. Snowball technique

The following people should be contacted and asked for the five most relevant studies on the research question. We will also look at their websites for relevant publications.

1. Jenn Yablonksi, UNICEF
2. Elena Gaia, UNICEF
3. Fabio Veras Soares, IPC
4. Norbert Schady, IADB
5. Orazio Attansio, UCL
6. Carine Clert, World Bank

Studies shared by experts will be assessed against Stage 1 and Stage 2 screening criteria. We will also check the reference lists of the studies obtained for any further studies that fit the inclusion criteria. 5. Websites searches

The following websites/search engines should be consulted, if possible using the same search strings as for the academic databases. Any studies found on these websites will be assessed against the same Stage 1 and Stage 2 screening criteria.

- Google (the first five pages)
- World Bank
- R4D DFID
- International Policy Centre for Inclusive Growth (IPC-IG)
- International Food Policy Research Institute (IFPRI)
- GSDRC
- OPM website
- Transfer Project (UNC Chapel Hill)
- ECLAC/CEPAL
- IADB website
- ADB website
- IDS website
- BLDS website
- Social Science Research Network

6. Classification of studies

Studies that have passed both screening stages will be classified and described in an annotated bibliography. The classification tables will include the following information:

- authors and year of study
- geographical coverage
- detailed description of intervention and context
- population
- methods, sampling and data
- summary findings on design and implementation factor Part 2. Study assessment tools

As described in detail in Chapter 4, in the second stage of screening of the studies retrieved, separate tools were used to assess studies for risk of bias (for counterfactual impact analysis studies) and quality (for qualitative papers, considered under the searches for studies on the links between policy design and implementation factors and outcomes). Both tools are reported below.

Table A2.1 Proposed framework for assessing risk of bias for quantitative impact studies

| Domain | Key questions to consider | Criteria for judging risk of bias | Risk of bias | |-------------------------------|------------------------------------------------------------------------------------------|--------------------------------------------------------------------------------------------------|--------------| | Selection bias and confounding| • Does the comparison group provide a reliable counterfactual? | Random assignment to treatment and comparison, differences not greater than expected by chance and units of random assignment match units of analysis. Extensive information on equivalence of treatment and control groups, only minor differences exist and adequate attempts to deal with differences in observables and unobservables. | Low | | | • Are all relevant observable and unobservable differences between groups accounted for? | Information on equivalence of groups but obvious differences exist for important variables and no / inadequate attempt to correct for selection bias. No information on group equivalence. | High | | Attrition bias | Is any non-random attrition in the sample a threat to validity? | Careful statistical controls used for effects of attrition, or attrition is minimal so that danger of differential attrition is addressed. Possible differential attrition between intervention and control is identified and discussed and is not likely to lead to significant bias. | Low | | | | Attrition from treatment or comparison group is moderate or high (~30% or more) and no attempt to determine effects of attrition on outcomes. | High | | Statistical significance | Are there biases leading to Type I or Type II errors? | No unit of analysis errors (e.g. account is taken for cluster survey design), heterogeneity between groups considered, sample size sufficiently large and regression addresses heteroscedasticity (e.g. robust standard errors). | Low | | | | Unit of analysis errors, no account for heterogeneity, insignificant results could be due to insufficient sample size and / or no account for heteroscedasticity. | High | | Other bias | Are results subject to other forms of bias? | Study appears to be largely free of other sources of bias. | Low | | | | There is at least one significant risk of bias in the study (e.g. performance bias, detection bias, outcome reporting bias, courtesy bias etc.) | High |

Source: Authors’ elaboration based on The Cochrane Collaboration Risk of Bias Tool (2011), Yoong et al. (2012) and Hombrados and Waddington (2012).

### Table A2.2 Framework for assessing rigour of qualitative, institutional analysis and descriptive studies considering design and implementation features

| Domain | Questions to guide assessment | Comment | Judgement (no concerns, some concerns, or major concerns) | |-------------------------------|------------------------------------------------------------------------------------------------|---------|----------------------------------------------------------| | Clarity and transparency of approach | Are there clear research questions or objectives set out either explicitly or implicitly? | | | | | Are the data/information sources and collection processes made clear? | | | | | Is there an analytical/ conceptual framework? | | | | | Are the approaches or methods of analysis discussed? | | | | | Is there a discussion of limitations of the evidence and what remains unknown or unclear? | | | | Credibility of findings | Do the conclusions logically follow from the data/information and analysis presented? | | | | | Is there a clear discussion of how assessments or judgements have been reached? | | | | | Is corroborating evidence used to support or refine findings? | | | | Acknowledgement of potential internal bias or limitations | Are all risks of bias among any subjects involved acknowledged (e.g. due to exaggeration, anecdotal reports, Hawthorne effects, sensitivity of issues discussed)? | | | | | Is potential bias among the researchers considered? | | | | External validity¹ | Is the methodological approach, including sample size and composition, appropriate to the level of claims made? | | | | | Is evidence given to support any claims of wider inference? | | | | | Is there a discussion of limitations of drawing wider inference? | | |

Source: Authors’ elaboration drawing on DFID (2014) and Spencer et al. (2003)

¹ Here we adopt the definition of Shadish et al. (2002) who define external validity as ‘inferences about whether cause–effect relationships hold over variation in persons, settings, treatment variables and measurement variables’. Annex 3 Summary table of searches and reasons for exclusion and flow diagrams

Table A3.1 below provides an overview of the number of studies at different stages of the review for each sub-question. The table shows studies retrieved from each of the sources as set out in the search protocols. Most studies were retrieved from bibliographic databases, ranging from 305 studies (question 2e) to 10,623 studies (question 1d). However, many of these were subsequently found to not be relevant and were excluded at Stage 1 screening. From the database searches, between 7 (2e) and 68 (2b) were included in the Stage 2 screening.

The table also shows the number of studies retrieved from other sources, including website searches, review studies and snowballing, and expert suggestions. Studies identified as relevant from other sub-questions were also included. A comparatively high number of studies were retrieved from websites, where the emphasis was placed on retrieving the grey literature, with as many as 79 (1a) studies retrieved. With regards to responses from experts, when asked to suggest seminal studies on the subject, we received up to 9 (1a, 1b, 1c and 1e) relevant references, and for some of the sub-questions we did not receive any relevant suggestions (2a, 2e and 2f). The final column in Table A3.1 indicates the total number of studies that underwent risk of bias / quality assessment.

The flow diagrams that follow Table A3.1 provide a detailed summary of the number of studies that passed through the different stages for each sub-question, from retrieval to assessment. These are then followed by an accompanying set of tables that summarise the specific reasons for exclusion of studies from bibliographic databases during Stage 1 screening (Tables A3.2a, A3.2b, A3.3a, A3.3b). As can be seen, the main reasons for exclusion during the title and abstract screening relate to the intervention (64% of those excluded for studies under 1a to 1f and 86% for 2a to 2f). During full text screening, the study design was one of the main reasons for exclusion, along with studies being relevant instead for other sub-questions (for studies identified under 2d and 2f).

As highlighted in the flow diagrams, a number of studies were also excluded during stage Two screening on account of them not meeting all of the original inclusion criteria. The main reason for studies being excluded at this stage was linked to the study design not meeting the basic inclusion criteria (around three quarters of all cases). After that, 8% were excluded for not reporting on the outcome or design and implementation feature being considered. In order of importance, other reasons for exclusion included no access (6%), the intervention (5%), geographical location (4%), being a remaining duplicate (2%) and language (1%).

For sub-questions 1c to 1f, a Text Mining tool in the EPPI software was used in order to assist in screening studies. In brief, the approach involves carrying out the first stage of screening to a random sample of at least 1,000 studies. The text mining tool then uses information from these studies and, based on the screening decisions made, identifies relevant studies for further screening, upon which manual screening is carried out. Further details of how this process was implemented is provided in Chapter 4. As regards to the flow diagrams, details are therefore given in the diagrams for questions 1c to 1f of the number of studies excluded through the Text Mining process.

Table A3.1: Overview of studies retrieved by source and passing through different stages of assessment

| Question | Database retrieval | Database studies: Stage 1 Screening | Studies retrieved from other sources | |----------|--------------------|-------------------------------------|-------------------------------------| | | Studies retrieved after initial de-duplication | Additional duplicates | Total screened at Title & Abstract | Studies excluded at Title & Abstract | Studies excluded at Full Text | Database studies entering Stage 2 Screening | Papers retrieved: Websites | Papers retrieved: Review studies & snowballing | Papers retrieved: Expert suggestions | Papers retrieved: From other sub-questions | Studies undergoing Risk of Bias assessment | | Q1a | 4,956 | 106 | 4,850 | 4,615 | 183 | 52 | 79 | 10 | 9 | 27 | 75 | | Q1b | 950 | 4 | 946 | 829 | 52 | 65 | 57 | 16 | 9 | 136 | 120 | | Q1c | 4,197 | 60 | 4,137 | 4,068 | 10 | 59 | 59 | 10 | 9 | 30 | 125 | | Q1d | 10,623 | 64 | 10,559 | 10,509 | 32 | 18 | 34 | 2 | 7 | 6 | 42 | | Q1e | 5,865 | 8 | 5,859 | 5,765 | 48 | 48 | 39 | 4 | 9 | 54 | 93 | | Q1f | 4,080 | 9 | 4,051 | 3,977 | 20 | 54 | 24 | 3 | 8 | 120 | 56 | | Q2a | 561 | 2 | 559 | 476 | 30 | 53 | 23 | 1 | 0 | 51 | 41 | | Q2b | 1,671 | 7 | 1,664 | 1,559 | 37 | 68 | 8 | 0 | 2 | 7 | 25 | | Q2c | 742 | 4 | 738 | 652 | 32 | 54 | 21 | 0 | 1 | 10 | 10 | | Q2d | 1,906 | 3 | 1,903 | 1,800 | 81 | 22 | 12 | 0 | 1 | 4 | 14 | | Q2e | 305 | 0 | 305 | 297 | 1 | 7 | 5 | 0 | 0 | 3 | 2 | | Q2f | 1,533 | 3 | 1,530 | 1,466 | 35 | 29 | 7 | 1 | 0 | 43 | 21 |

Key for sub-questions: 1a = monetary poverty and inequality; 1b = education; 1c = health and nutrition; 1d = savings, investment and production; 1e = employment; 1f = empowerment; 2a = core design features; 2b = conditionalities; 2c = targeting features; 2d = payment systems; 2e = grievance mechanisms and programme governance; 2f = complementary interventions and supply-side services. Figure A3.1 Flow diagram for question 1a on monetary poverty

Studies retrieved from database search following initial de-duplication (n = 4,956)

Further duplicates removed (n = 106)

Studies from database search screened by title and abstract (n = 4,850)

Studies excluded (n = 4,615)

Studies from database search screened at full text (n = 235)

Studies excluded (n = 183)

Studies from database search entering stage two screening (n = 52)

Studies excluded (n = 102)

Studies retrieved from other sources (n = 125), including:

- Websites (n = 79)
- Snowballing (n = 10)
- Expert suggestions (n = 9)
- From other sub-questions (n = 27)

Studies undergoing Risk of Bias / Quality Assessment (n = 75)

Studies passing (n = 34)

Final studies reporting on selected indicators (n = 44)

Additional “passed” studies identified as relevant from other sub-questions (n = 27)

Total number of studies considered for extraction under this outcome (n = 61) Figure A3.2 Flow diagram for question 1b on education

Studies retrieved from database search following initial de-duplication (n = 950)

Further duplicates removed (n = 4)

Studies from database search screened by title and abstract (n = 946)

Studies excluded (n = 829)

Studies from database search screened at full text (n = 117)

Studies excluded (n = 52)

Studies from database search entering stage two screening (n = 65)

Studies retrieved from other sources (n = 218), including:

- Websites (n = 57)
- Snowballing (n = 16)
- Expert suggestions (n = 9)
- From other sub-questions (n = 136)

Studies undergoing Risk of Bias / Quality Assessment (n=120)

Studies excluded (n = 163)

Studies passing (n = 74)

Final studies reporting on selected indicators (n = 42)

Additional “passed” studies identified as relevant from other sub-questions (n = 25)

Total number of studies considered for extraction under this outcome (n = 99) Figure A3.3 Flow diagram for question 1c on health and nutrition

Studies retrieved from database search following initial de-duplication (n = 4,197)

Studies from database search screened by title and abstract using Text Mining (n = 4,137)

Studies from database search screened at full text (n = 69)

Studies from database search entering stage two screening (n = 59)

Studies retrieved from other sources (n = 108), including:

- Websites (n = 59)
- Snowballing (n = 10)
- Expert suggestions (n = 9)
- From other sub-questions (n = 30)

Studies undergoing Risk of Bias / Quality Assessment (n=125)

Studies passing (n = 64)

Final studies reporting on selected indicators (n = 41)

Additional “passed” studies identified as relevant from other sub-questions (n = 25)

Total number of studies considered for extraction under this outcome (n = 89) Figure A3.4 Flow diagram for question 1d on investment, savings and production

Studies retrieved from database search following initial de-duplication (n = 10,623)

Further duplicates removed (n = 64)

Studies from database search screened by title and abstract using Text Mining (n = 10,559)

Excluded through initial screening (n = 1,527) Excluded through Text Mining (n = 8,982) Total excluded (n = 10,509)

Studies from database search screened at full text (n = 50)

Studies excluded at full text (n = 32)

Studies from database search entering stage two screening (n = 18)

Studies retrieved from other sources (n = 49), including:

- Websites (n = 34)
- Snowballing (n = 2)
- Expert suggestions (n = 7)
- From other sub-questions (n = 6)

Studies undergoing Risk of Bias / Quality Assessment (n=42)

Studies excluded (n = 25)

Studies passing (n = 32)

Final studies reporting on selected indicators (n = 27)

Additional “passed” studies identified as relevant from other sub-questions (n = 5)

Total number of studies considered for extraction under this outcome (n = 37) Figure A3.5 Flow diagram for question 1e on employment

Studies retrieved from database search following initial de-duplication (n = 5,865)

Further duplicates removed (n = 6)

Studies from database search screened by title and abstract using Text Mining (n = 5,859)

Excluded through initial screening (n = 1,122) Excluded through Text Mining (n = 4,643) Total excluded (n = 5,765)

Studies from database search screened at full text (n = 94)

Studies excluded at full text (n = 46)

Studies from database search entering stage two screening (n = 48)

Studies retrieved from other sources (n = 106), including:

- Websites (n = 39)
- Snowballing (n = 4)
- Expert suggestions (n = 9)
- From other sub-questions (n = 54)

Studies undergoing Risk of Bias / Quality Assessment (n=93)

Studies excluded (n = 60)

Studies passing (n = 61)

Final studies reporting on selected indicators (n = 74)

Additional “passed” studies identified as relevant from other sub-questions (n = 19)

Total number of studies considered for extraction under this outcome (n = 80) Figure A3.6 Flow diagram for question 1f on empowerment

Studies retrieved from database search following initial de-duplication (n = 4,060)

Further duplicates removed (n = 9)

Studies from database search screened by title and abstract using Text Mining (n = 4,051)

Excluded through initial screening (n = 1,204) Excluded through Text Mining (n = 2,773) Total excluded (n = 3,977)

Studies from database search screened at full text (n = 74)

Studies excluded at full text (n = 20)

Studies from database search entering stage two screening (n = 54)

Studies retrieved from other sources (n = 155), including:

- Websites (n = 24)
- Snowballing (n = 3)
- Expert suggestions (n = 8)
- From other sub-questions (n = 120)

Studies undergoing Risk of Bias / Quality Assessment (n=56)

Studies excluded (n = 153)

Studies passing (n = 36)

Final studies reporting on selected indicators (n = 31)

Additional “passed” studies identified as relevant from other sub-questions (n = 18)

Total number of studies considered for extraction under this outcome (n = 54) Figure A3.7 Flow diagram for question 2a on core design parameters

Studies retrieved from database search following initial de-duplication (n = 561)

Further duplicates removed (n = 2)

Studies from database search screened by title and abstract (n = 559)

Studies excluded (n = 476)

Studies from database search screened at full text (n = 83)

Studies excluded (n = 30)

Studies from database search entering stage two screening (n = 53)

Studies retrieved from other sources (n = 75), including:

- Websites (n = 23)
- Snowballing (n = 1)
- Expert suggestions (n = 0)
- From other sub-questions (n = 51)

Studies undergoing Risk of Bias / Quality Assessment (n = 42)

Studies excluded (n = 86)

Studies passing (n = 25)

Final studies from which evidence extracted (across all outcome areas) (n = 40)

Additional “passed” studies identified as relevant from other sub-questions (n = 16)

Total number of studies considered for extraction under this outcome (n = 41) Figure A3.8 Flow diagram for question 2b on conditionality

Studies retrieved from database search following initial de-duplication (n = 1,671)

Further duplicates removed (n = 7)

Studies from database search screened by title and abstract (n = 1,664)

Studies excluded (n = 1,559)

Studies from database search screened at full text (n = 105)

Studies excluded (n = 37)

Studies from database search entering stage two screening (n = 68)

Studies excluded (n = 60)

Studies retrieved from other sources (n = 17), including:

- Websites (n = 8)
- Snowballing (n = 0)
- Expert suggestions (n = 2)
- From other sub-questions (n = 7)

Studies undergoing Risk of Bias / Quality Assessment (n = 25)

Studies passing (n = 19)

Final studies from which evidence extracted (across all outcome areas) (n = 11)

Additional “passed” studies identified as relevant from other sub-questions (n = 2)

Total number of studies considered for extraction under this outcome (n = 21) Figure A3.9 Flow diagram for question 2c on targeting

Studies retrieved from database search following initial de-duplication (n = 742)

Further duplicates removed (n = 4)

Studies from database search screened by title and abstract (n = 738)

Studies excluded (n = 652)

Studies from database search screened at full text (n = 86)

Studies excluded (n = 32)

Studies from database search entering stage two screening (n = 54)

Studies retrieved from other sources (n = 32), including:

- Websites (n = 21)
- Snowballing (n = 0)
- Expert suggestions (n = 1)
- From other sub-questions (n = 10)

Studies undergoing Risk of Bias / Quality Assessment (n = 10)

Studies excluded (n = 76)

Studies passing (n = 6)

Final studies from which evidence extracted (across all outcome areas) (n = 1)

Additional “passed” studies identified as relevant from other sub-questions (n = 1)

Total number of studies considered for extraction under this outcome (n = 7) Figure A3.10 Flow diagram for question 2d on payment systems

Studies retrieved from database search following initial de-duplication (n = 1,906)

Further duplicates removed (n = 3)

Studies from database search screened by title and abstract (n = 1,903)

Studies excluded (n = 1,800)

Studies from database search screened at full text (n = 103)

Studies excluded (n = 81)

Studies from database search entering stage two screening (n = 22)

Studies retrieved from other sources (n = 18), including:

- Websites (n = 13)
- Snowballing (n = 0)
- Expert suggestions (n = 1)
- From other sub-questions (n = 4)

Studies undergoing Risk of Bias / Quality Assessment (n = 14)

Studies passing (n = 4)

Final studies from which evidence extracted (across all outcome areas) (n = 2)

Additional “passed” studies identified as relevant from other sub-questions (n = 0)

Total number of studies considered for extraction under this outcome (n = 4) Figure A3.11 Flow diagram for question 2e on grievance mechanisms and programme governance

Studies retrieved from database search following initial de-duplication (n = 305)

Further duplicates removed (n = 0)

Studies from database search screened by title and abstract (n = 305)

Studies excluded (n = 297)

Studies from database search screened at full text (n = 8)

Studies excluded (n = 1)

Studies from database search entering stage two screening (n = 7)

Studies retrieved from other sources (n = 8), including:

- Websites (n = 5)
- Snowballing (n = 0)
- Expert suggestions (n = 0)
- From other sub-questions (n = 3)

Studies undergoing Risk of Bias / Quality Assessment (n = 2)

Studies passing (n = 0)

Final studies from which evidence extracted (across all outcome areas) (n = 0)

Additional “passed” studies identified as relevant from other sub-questions (n = 0)

Total number of studies considered for extraction under this outcome (n = 0) Figure A3.12 Flow diagram for question 2f on complementary interventions and supply-side services

Studies retrieved from database search following initial de-duplication (n = 1,533)

Further duplicates removed (n = 3)

Studies from database search screened by title and abstract (n = 1,530)

Studies excluded (n = 1466)

Studies from database search screened at full text (n = 64)

Studies excluded (n = 35)

Studies from database search entering stage two screening (n = 29)

Studies retrieved from other sources (n = 51), including:

- Websites (n = 7)
- Snowballing (n = 1)
- Expert suggestions (n = 0)
- From other sub-questions (n = 43)

Studies undergoing Risk of Bias / Quality Assessment (n = 21)

Studies excluded (n = 59)

Studies passing (n = 11)

Final studies from which evidence extracted (across all outcome areas) (n = 8)

Additional “passed” studies identified as relevant from other sub-questions (n = 3)

Total number of studies considered for extraction under this outcome (n = 14) Tables summarising reasons for exclusion (studies retrieved from bibliographic database searches)

### Table A3.2a. Reasons for exclusion: Stage 1 screening Title and Abstract (sub-questions 1a-1f)

| Total screened at Title & Abstract | Date | Language | Population | Geographical location | Intervention | Study design | Outcome | Relevant for different sub-question | Review study | Exclude on text mining | Sub total | Exclude | Total excluded | Total screened at full text | |-----------------------------------|------|----------|------------|-----------------------|--------------|--------------|---------|-------------------------------------|--------------|------------------------|-----------|---------|----------------|--------------------------| | Q1a | 4,850| 0 | 1 | 0 | 170 | 3894 | 75 | 78 | 384 | 3 | 4615 | NA | 4615 | 235 | | Q1b | 946 | 0 | 0 | 1 | 21 | 726 | 20 | 17 | 42 | 2 | 829 | NA | 829 | 117 | | Q1c | 4,137| 2 | 0 | 312 | 103 | 395 | 181 | 731 | 8 | 49 | 1773 | 2295 | 4068 | 69 | | Q1d | 10,559| 0 | 0 | 2 | 22 | 1095 | 73 | 39 | 293 | 3 | 1527 | 8982 | 10509 | 50 | | Q1e | 5,859| 0 | 0 | 0 | 40 | 892 | 35 | 34 | 121 | 0 | 1122 | 4643 | 5765 | 94 | | Q1f | 4,051| 0 | 0 | 39 | 66 | 106 | 107 | 845 | 27 | 14 | 1204 | 2773 | 3977 | 74 | | Totals | 30,402| 2 | 1 | 354 | 422 | 7108 | 491 | 1744 | 877 | 71 | 11070 | 18693 | 29763 | 639 | | % of subtotal excluded | 0% | 0% | 3% | 4% | 64% | 4% | 16% | 8% | 1% | | 0% | 0% | 0% | 1% |

### Table A3.2b. Reasons for exclusion: Stage 1 screening Title and Abstract (sub-questions 2a-2f)

| Total screened at Title & Abstract | Date | Language | Population | Geographical location | Intervention | Study design | Design / implementation feature | Relevant for different sub-question | Review study | Analysis | Total excluded | Total screened at full text | |-----------------------------------|------|----------|------------|-----------------------|--------------|--------------|---------------------------------|-------------------------------------|--------------|---------|----------------|--------------------------| | Q2a | 559 | 0 | 0 | 1 | 21 | 287 | 52 | 6 | 94 | 4 | 11 | 476 | | Q2b | 1664 | 0 | 4 | 0 | 61 | 1295 | 83 | 12 | 99 | 2 | 3 | 1558 | | Q2c | 738 | 0 | 1 | 0 | 15 | 493 | 62 | 23 | 34 | 1 | 23 | 652 | | Q2d | 1,903| 0 | 0 | 0 | 27 | 1706 | 53 | 13 | 0 | 1 | 0 | 1800 | | Q2e | 305 | 0 | 0 | 0 | 11 | 273 | 5 | 4 | 4 | 0 | 0 | 297 | | Q2f | 1,530| 0 | 2 | 0 | 81 | 1297 | 46 | 16 | 24 | 0 | 0 | 1466 | | Totals | 6699 | 0 | 7 | 1 | 216 | 5351 | 301 | 74 | 255 | 8 | 37 | 6250 | | % of subtotal excluded | 0% | 0% | 0% | 3% | 86% | 5% | 1% | 4% | 0% | 0% | 1% | 1% |

### Table A3.3a. Reasons for exclusion: Stage 1 screening Full Text (sub-questions 1a-1f)

| Total screened at Full Text | Date | Language | Population | Geographical location | Intervention | Study design | Outcome | Relevant for different sub-question | Additional duplicate | Review study | No access | Total excluded | Total entering Stage 2 screening | |-----------------------------|------|----------|------------|-----------------------|--------------|--------------|---------|-------------------------------------|----------------------|-------------|-----------|----------------|-------------------------------| | 01a | 235 | 0 | 0 | 0 | 3 | 7 | 107 | 13 | 0 | 0 | 53 | 0 | 183 | | 01b | 117 | 0 | 3 | 0 | 0 | 3 | 22 | 5 | 0 | 2 | 8 | 9 | 52 | | 01c | 69 | 0 | 0 | 0 | 0 | 0 | 10 | 0 | 0 | 0 | 0 | 0 | 10 | | 01d | 50 | 0 | 0 | 0 | 0 | 0 | 17 | 9 | 0 | 1 | 5 | 0 | 32 | | 01e | 94 | 0 | 1 | 0 | 1 | 4 | 27 | 4 | 0 | 2 | 0 | 7 | 46 | | 01f | 74 | 0 | 0 | 0 | 0 | 0 | 18 | 2 | 0 | 0 | 0 | 0 | 20 | | Totals | 639 | 0 | 4 | 0 | 4 | 14 | 201 | 33 | 0 | 5 | 66 | 16 | 343 | | % of total excluded | 0% | 1% | 0% | 1% | 4% | 59% | 10% | 0% | 1% | 19% | 5% | 5% | 296 |

### Table A3.3b. Reasons for exclusion: Stage 1 screening Full Text (sub-questions 2a-2f)

| Total screened at Full Text | Date | Language | Population | Geographical location | Intervention | Study design | Design / Implementation factor | Relevant for different sub-question | Additional duplicate | Analysis | No access | Total excluded | Total entering Stage 2 screening | |-----------------------------|------|----------|------------|-----------------------|--------------|--------------|-------------------------------|-------------------------------------|----------------------|----------|-----------|----------------|-------------------------------| | 02a | 83 | 0 | 0 | 0 | 1 | 2 | 8 | 12 | 0 | 0 | 4 | 3 | 30 | | 02b | 105 | 0 | 0 | 0 | 0 | 0 | 12 | 6 | 0 | 0 | 14 | 5 | 37 | | 02c | 86 | 0 | 0 | 0 | 0 | 0 | 11 | 7 | 0 | 0 | 8 | 6 | 32 | | 02d | 103 | 0 | 0 | 0 | 0 | 0 | 1 | 3 | 4 | 67 | 3 | 1 | 2 | | 02e | 8 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | | 02f | 64 | 0 | 0 | 0 | 0 | 0 | 2 | 3 | 0 | 24 | 0 | 3 | 35 | | Totals | 449 | 0 | 0 | 0 | 1 | 5 | 38 | 29 | 91 | 3 | 30 | 19 | 216 | | % of total excluded | 0% | 0% | 0% | 0% | 2% | 18% | 13% | 42% | 1% | 14% | 9% | 9% | 233 | Annex 4 Summary of the evidence base

This annex summarises the evidence base, both in terms of the full list of studies that passed the inclusion criteria and the screening for risk of bias and quality assessment therefore making it to the annotated bibliography and, within those, those studies from which evidence was extracted on the selected indicators that were reviewed.

The tables below summarise the evidence base across the following dimensions:

- Source of retrieval (Table A4.1)
- Type of study (Table A4.2)
- Geographical coverage for the full list of studies (Table A4.3)
- Geographical and programme coverage for the studies included at the data extraction stage (Tables A4.4-A4.9)

### Table A4.1 Full list of studies by source of retrieval

| Outcome areas | Bibliographic databases | Websites | Review studies | Expert recommendations | Other sub-questions | Total | |--------------------------------------|-------------------------|----------|----------------|------------------------|---------------------|-------| | Poverty | 16 | 3 | 4 | 6 | 32 | 61 | | Education | 6 | 13 | 10 | 8 | 62 | 99 | | Health and nutrition | 30 | 12 | 6 | 4 | 37 | 89 | | Savings, investment and production | 14 | 9 | 2 | 6 | 6 | 37 | | Employment | 16 | 16 | 2 | 7 | 39 | 80 | | Empowerment | 3 | 5 | 2 | 7 | 37 | 54 |

### Design and implementation features

| Core design features | 7 | 2 | 1 | 0 | 31 | 41 | | Conditionality | 17 | 1 | 0 | 0 | 3 | 21 | | Targeting | 5 | 0 | 0 | 1 | 1 | 7 | | Payment mechanisms | 1 | 1 | 0 | 1 | 0 | 3 | | Grievance mechanisms and programme governance | 0 | 0 | 0 | 0 | 0 | 0 | | Complementary interventions and supply-side services | 1 | 1 | 0 | 0 | 12 | 14 |

Note: studies retrieved from ‘other sub-questions’ were studies that met the inclusion criteria and passed the risk of bias or quality assessment screening but were retrieved under a different sub-question. In some cases they were relevant for that other sub-question and in other cases they were not.

### Table A4.2 Full list of studies by type of paper

| Outcome areas | Peer reviewed journal articles | Working papers | Reports and formal evaluations | Unpublished papers | PhD theses | Book chapters | Total | |--------------------------------------|--------------------------------|----------------|-------------------------------|--------------------|------------|---------------|-------| | Poverty | 17 | 16 | 10 | 8 | 10 | 0 | 61 | | Education | 39 | 25 | 11 | 12 | 11 | 1 | 99 | | Health and nutrition | 44 | 13 | 10 | 11 | 11 | 0 | 89 | | Savings, investment and production | 10 | 9 | 4 | 7 | 7 | 0 | 37 | | Employment | 29 | 22 | 9 | 7 | 12 | 1 | 80 | | Empowerment | 26 | 11 | 4 | 5 | 7 | 1 | 54 |

### Design and implementation features

| Core design features | 20 | 9 | 6 | 3 | 3 | 0 | 41 | | Conditionality | 12 | 9 | 0 | 0 | 0 | 0 | 21 | | Targeting | 2 | 3 | 0 | 1 | 1 | 0 | 7 | | Payment mechanisms | 1 | 1 | 0 | 0 | 1 | 0 | 3 | | Grievance mechanisms and programme governance | 0 | 0 | 0 | 0 | 0 | 0 | 0 | | Complementary interventions and supply-side services | 8 | 5 | 0 | 0 | 1 | 0 | 14 |

Note: Unpublished papers is a residual category for unpublished studies that were not written as working papers, reports or evaluations (e.g. unpublished studies produced by an academic department of a university).

### Table A4.3 Geographical coverage (among full list of studies)

| Outcome areas | Sub-Saharan Africa | East Asia & Pacific | Europe & Central Asia | Latin America & Caribbean | Middle East & North Africa | South Asia | Total | |--------------------------------|--------------------|---------------------|-----------------------|---------------------------|---------------------------|------------|-------| | Poverty | 23 | 3 | 2 | 33 | 0 | 2 | 63 | | Education | 23 | 7 | 2 | 65 | 2 | 3 | 102 | | Health and nutrition | 28 | 1 | 1 | 62 | 0 | 3 | 95 | | Savings, investment and production | 21 | 0 | 1 | 14 | 0 | 1 | 37 | | Employment | 23 | 4 | 2 | 52 | 1 | 2 | 84 | | Empowerment | 21 | 1 | 1 | 35 | 0 | 2 | 60 |

#### Design and implementation features

| Core design features | 12 | 5 | 0 | 24 | 1 | 1 | 43 | | Conditionality | 7 | 1 | 0 | 11 | 1 | 0 | 20 | | Targeting | 3 | 1 | 0 | 2 | 1 | 0 | 7 | | Payment mechanisms | 2 | 0 | 0 | 0 | 0 | 1 | 3 | | Grievance mechanisms and programme governance | 0 | 0 | 0 | 0 | 0 | 0 | 0 | | Complementary interventions and supply-side services | 4 | 0 | 0 | 10 | 0 | 0 | 14 |

Note: Figures based on countries covered by studies and so will not exactly match with other tables as some studies report on multiple interventions and/or countries.

### Table A4.4 Geographical and programme coverage among studies from which evidence extracted – Latin America and Caribbean

| Region / country | Programme | Poverty | Education | Health and nutrition | Savings, investment and production | Employment | Empowerment | |------------------|-----------|---------|-----------|----------------------|-----------------------------------|------------|-------------| | **Latin America & Caribbean** | | | | | | | | | Bolivia | Bonosol pension | 1 | 1 | | | | | | Bolivia | Bolivida | | | | | | 1 | | Brazil | Bolsa Alimentação | 1 | | | | | | | Brazil | Bolsa Escola | | | | | | 1 | | Brazil | Bolsa Família | | | | | | 3 | | Brazil | Beneficio de Prestação Continuada (BPC) | 1 | | | | | 1 | | Colombia | Familias en Acción | 2 | 5 | 2 | | | 4 | | Colombia | Subsidios Condicionados a la Asistencia Escolar (SCAE) | 2 | | | | | 2 | | Dominican Republic | Solidarity Programme | | | | | | 1 | | Ecuador | Bono de Desarrollo Humano (BDH) | 2 | 7 | 3 | 3 | 1 | | | Ecuador | WFP Colombian refugee RCT (WFP CT) | 1 | | | 2 | | 2 | | El Salvador | Comunidades Solidarias Rurales (CSR) | 1 | | | | | 1 | | Honduras | Programa de Asignación Familiar (PRAF) | 2 | 1 | | 5 | | 2 | | Honduras | Bono 10,000 | | | | | | 1 | | Jamaica | Programme of Advancement Through Health and Education (PATH) | | | | | | 1 | | Mexico | PROGRESA / Oportunidades | 6 | 19 | 12 | 5 | 13 | 8 | | Mexico | PROCAMPO | 1 | 2 | 1 | 1 | | | | Mexico | Programa Apoyo Alimentario (PAL) | 2 | | | 1 | | | | Mexico | Programa de Atención a Adultos Mayores en Zonas Rurales | | | | | | 1 | | Nicaragua | Red de Protección Social (RPS) | 4 | 7 | 4 | 1 | 8 | 3 | | Nicaragua | Atención a Crisis | 2 | 3 | 1 | 1 | 5 | | | Paraguay | Teleporã | | | | | | 1 | | Peru | Juntos | 1 | 1 | 1 | | 1 | 2 | | **TOTALS** | | 24 | 51 | 30 | 9 | 49 | 19 |

*Note: Totals do not always exactly correspond to number of unique studies from which evidence extracted as some studies report on more than one intervention.*

### Table A4.5 Geographical and programme coverage among studies from which evidence extracted – Sub-Saharan Africa

| Region / country | Programme | Poverty | Education | Health and nutrition | Savings, investment and production | Employment | Empowerment | |------------------|-----------|---------|-----------|----------------------|-----------------------------------|------------|-------------| | **Sub-Saharan Africa** | | | | | | | | | Burkina Faso | Nahouri Cash Transfers Pilot Project | 1 | 1 | | | | | | Ghana | Innovation for poverty randomised trial | 1 | 1 | | | | | | Ghana | Livelihood empowerment against poverty (LEAP) | 1 | 2 | | | 1 | 2 | | Kenya | Give Directly experiment | 1 | | | | 1 | 1 | | Kenya | Hunger Safety Net Programme (HSNP) | 1 | 1 | 1 | | 1 | 1 | | Kenya | Orphan and Vulnerable Children Cash Transfer (OVC-CT) | 1 | 1 | 1 | | 1 | 1 | | Lesotho | Child Grant Programme | 1 | 1 | 1 | 2 | 2 | | | Malawi | Social Cash Transfer Programme (SCTP) | 1 | 2 | 1 | 1 | 2 | | | Malawi | The Zomba Cash Transfer Programme | 5 | | | | | 3 | | Malawi | Sexual health incentive study | 1 | | | | | | | Niger | Prospective study with Forum Santé Niger and Médecins Sans Frontières | 1 | | | | | | | Niger | Concern Worldwide drought-response unconditional transfer | 2 | | | | 2 | | | South Africa | Old Age Pension | 1 | | | | 3 | 1 | | South Africa | Child Support Grant and Foster Grant | 1 | | | | | | | Tanzania | Tanzania Social Action Fund (TSAF) | 1 | 1 | | | | | | Uganda | WFP Karamoja cash transfer | 1 | 1 | 1 | | | | | Uganda | Youth Opportunities Programme (YOP) | 1 | | | | 2 | 2 | | Uganda | Social Assistance Grants for Empowerment (SAGE) | 1 | 1 | 1 | | 1 | 1 | | Uganda | Women’s Income Generating Support (WINGS) | 1 | | | | 1 | 2 | | Zambia | Monze Cash Transfer Pilot | 1 | 1 | 1 | | 1 | | | Zambia | Child Grant Programme | 1 | 1 | 1 | 2 | 2 | | | **TOTALS** | | 12 | 19 | 11 | 15 | 18 | 14 |

### Table A4.6 Geographical and programme coverage among studies from which evidence extracted – Middle East and North Africa

| Region / country | Programme | Poverty | Education | Health and nutrition | Savings, investment and production | Employment | Empowerment | |---------------------------|-----------|---------|-----------|----------------------|------------------------------------|------------|-------------| | Middle East & North Africa| | | | | | | | | Morocco | Taysir | 0 | 1 | 0 | 0 | 1 | 0 | | **TOTALS** | | 0 | 1 | 0 | 0 | 1 | 0 |

### Table A4.7 Geographical and programme coverage among studies from which evidence extracted – Europe and Central Asia

| Region / country | Programme | Poverty | Education | Health and nutrition | Savings, investment and production | Employment | Empowerment | |---------------------------|-----------|---------|-----------|----------------------|------------------------------------|------------|-------------| | Europe & Central Asia | | | | | | | | | Albania | Ndhima Ekonomike | 1 | 1 | 0 | 1 | | | | Kazakhstan | Bota programme | 1 | 1 | 1 | 1 | | | | Turkey | Social Risk Mitigation Project | 1 | | | | | | | **TOTALS** | | 2 | 2 | 0 | 1 | 2 | 1 |

### Table A4.8 Geographical and programme coverage among studies from which evidence extracted – South Asia

| Region / country | Programme | Poverty | Education | Health and nutrition | Savings, investment and production | Employment | Empowerment | |---------------------------|-----------|---------|-----------|----------------------|------------------------------------|------------|-------------| | South Asia | | | | | | | | | Bangladesh | Shombob | 1 | 1 | 1 | | | | | Pakistan | The Punjab Female School Stipend Program | 1 | | | | | | | Pakistan | The Benazir Income Support Programme | 1 | 1 | 1 | 1 | 1 | 1 | | **TOTALS** | | 2 | 3 | 2 | 1 | 2 | 1 |

### Table A4.9 Geographical and programme coverage among studies from which evidence extracted – East Asia and Pacific

| Region / country | Programme | Poverty | Education | Health and nutrition | Savings, investment and production | Employment | Empowerment | |---------------------------|-----------|---------|-----------|----------------------|------------------------------------|------------|-------------| | East Asia and Pacific | | | | | | | | | Cambodia | CESSP Scholarship Program (CSP) | 1 | | | | | | | Cambodia | Japan Fund for Poverty Reduction (JFPR) scholarship program | 1 | | | | | | | China | Junior High School Randomised Controlled Trial | 1 | | | | | | | Indonesia | Program Keluarga Harapan (PKH) | 1 | 1 | 1 | 1 | | | | Indonesia | Temporary UCT | 1 | | | | | | | Indonesia | Indonesia Bantuan Siswa Miskin (BSM) cash transfer for poor students | 1 | | | | | | | **TOTALS** | | 2 | 4 | 1 | 0 | 4 | 0 | Annex 5 Evidence: results tables for overall effects disaggregated by gender, and cash transfer design and implementation effects

This annex provides detailed tables of the results disaggregated by gender and design and implementation effects. These are reported for each of the six outcome areas under review.

A5.1 Poverty A5.1.1 Summary of results for cash transfer effects disaggregated by gender for monetary poverty indicators

A5.1.2 Summary of results for the role of cash transfer design and implementation parameters on monetary poverty

A5.2 Education A5.2.1 Summary of results for cash transfer effects disaggregated by gender for education indicators

A5.2.2 Summary of results for the role of cash transfer design and implementation parameters on education

A5.3 Health and nutrition A5.3.1 Summary of results for cash transfer effects disaggregated by gender for health and nutrition indicators

A5.3.2 Summary of results for the role of cash transfer design and implementation parameters on health and nutrition A5.4 Savings, investment and production

A5.4.1 Summary of results for cash transfer effects disaggregated by gender for savings, investment and production indicators

A5.4.2 Summary of results for the role of cash transfer design and implementation parameters on savings, investment and production

A5.5 Employment

A5.5.1 Summary of results for overall cash transfer effect on adult labour participation – by gender

A5.5.2 Summary of results for overall cash transfer effect on intensity of adult work – by gender

A5.5.3 Summary of results for overall cash transfer effect on adult labour force participation – by sector and gender

A5.5.4 Summary of results for overall cash transfer effect on adult work intensity – by sector and gender

A5.5.5 Summary of results for overall cash transfer effect on child labour participation – by gender

A5.5.6 Summary of results for overall cash transfer effect on intensity of child labour – by gender

A5.5.7 Summary of results for cash transfer effect on child labour participation – by sector and gender

A5.5.8 Summary of results for cash transfer effect on child labour intensity – by sector and gender

A5.5.9 Summary of results for overall cash transfer effect on migration – by gender

A5.5.10 Effect of design and implementation features on adult employment outcomes

A5.5.11 Effect of design and implementation features on child labour outcomes

A5.6 Empowerment

A5.6.1 Summary of results for the role of cash transfer design and implementation parameters on empowerment

## Summary tables for results for Monetary Poverty

### A5.1.1 Summary of results for cash transfer effects disaggregated by gender for monetary poverty indicators

| # | Study | Programme | Indicator | Effect | Measure of change | Significance | Details | |----|------------------------------|-----------|------------------------------------------------|--------|-------------------|--------------|----------------------------------------------| | 1 | Blattman et al. (2013) | YDP (Uganda) | Individual short-term expenditure | 6.943 | Change in UGX | 1% | For male beneficiaries, compared to non-beneficiaries | | | | YDP (Uganda) | Individual short-term expenditure | 7.923 | Change in UGX | 5% | For female beneficiaries | | 2 | Edmonds and Schady (2012) | BOH (Ecuador) | Total annual household expenditure | -277.0 | Change in USD | NS | For households with girl beneficiaries, compared to non-beneficiaries | | | | BOH (Ecuador) | Total annual household expenditure | 13.89 | Change in USD | NS | For households with boy beneficiaries, compared to non-beneficiaries | | 3 | Green et al. (2015) | WINGS (Uganda) | Individual monthly non-durable consumption | 0.41 | Z-score | 1% | For female beneficiaries, compared to non-beneficiaries | | 4 | Handa et al. (2014) | LEAP (Ghana) | Total monthly total expenditure per equivalent adult | -1.27 | Change in Ghc | NS | For female-headed households, compared to non-beneficiaries | | | | LEAP (Ghana) | Total monthly food expenditure per equivalent adult | 1.87 | Change in Ghc | NS | For female-headed households, compared to non-beneficiaries | | | | LEAP (Ghana) | Total monthly food expenditure per equivalent adult | -7.51 | Change in Ghc | NS | For male-headed households, compared to non-beneficiaries | | | | LEAP (Ghana) | Total monthly total expenditure per equivalent adult | -8.96 | Change in Ghc | NS | For male-headed households, compared to non-beneficiaries | | 5 | Haushofer & Shapiro. (2013) | Give Directly CT (Kenya) | Monthly non-durable household expenditure | -2.74 | Change in USD | NS | For female beneficiaries, compared to male beneficiaries | | 6 | Martinez (2004) | Bonosol (Bolivia) | Monthly household food consumption | -14.327 | Change in Bolivianos | NS | For beneficiary households where the oldest member is female, compared to those where the oldest member is male |

Notes: Figures in bold indicate statistically significant coefficient. NS = not significant at 10% significance level or below

### A5.1.2 Summary of results for the role of cash transfer design and implementation parameters on monetary poverty

| # | Study | Programme | Indicator | Effect | Measure of change | Significance | Additional details | |----|--------------------------------------------|----------------------------|-----------------------------------------------|--------|-------------------|--------------|--------------------------------------------------------| | | Main recipient | | | | | | | | 1 | Haushofer & Shapiro (2013) | Give directly experiment (Kenya) | Total monthly non-durable expenditure | -2.74 | Change in USD | NS | Being a female beneficiary | | | Transfer levels | | | | | | | | 1 | Blattmann et al. (2013) | YOP (Uganda) | Log of real value of short term expenditures | 0.043 | Change in UGX | NS | Measures effect of log grant size per person for beneficiaries | | 2 | Davis et al. (2002) | PROGRESA (Mexico) | Total monthly consumption expenditure per capita | 0.406 | Change in pesos | 1% | Measures effect of transfer levels for total sample | | | | PROCAMPO (Mexico) | Total monthly consumption expenditure per capita | 0.702 | Change in pesos | 1% | Measures effect of transfer levels for total sample | | | | PROGRESA (Mexico) | Total food consumption expenditure per capita | 0.355 | Change in pesos | 1% | Measures effect of transfer levels for total sample | | | | PROCAMPO (Mexico) | Total food consumption expenditure per capita | 0.386 | Change in pesos | 1% | Measures effect of transfer levels for total sample | | 3 | Handa et al. (2009) | PROGRESA (Mexico) | Log total monthly household expenditure | 0.034 | Change in log points | 1% | Measures effect of transfer levels for total sample | | | | PROGRESA (Mexico) | Log food monthly household expenditure | 0.035 | Change in log points | 1% | Measures effect of transfer levels for total sample | | 4 | Haushofer & Shapiro (2013) | Give directly experiment (Kenya) | Monthly non-durable household expenditure | 20.37 | Change in USD | 10% | Measures effect of receiving large transfer (instead of small) | | | Transfer frequency | | | | | | | | 1 | Bazzi (2013) | Temporary UCT (Indonesia) | Growth in log total household expenditures per capita 2005-2006 | -0.091 | Growth in log points | 1% | Received transfer only once | | | | Temporary UCT (Indonesia) | Growth in log total household expenditures per capita 2005-2006 | 0.074 | Growth in log points | 5% | Receive transfer twice already | | 2 | Haushofer & Shapiro (2013) | Give directly experiment (Kenya) | Monthly non-durable household expenditure | -4.4 | Change in USD | NS | Receiving monthly instead of lump sum | | | Duration of exposure | | | | | | | | 1 | AIR (2014) | ZCGP (Zambia) | Per capital monthly total expenditure | -4 | Change in Zk | NS | Difference between impact after 24 months and impact after 36 months | | | | ZCGP (Zambia) | Per capital monthly food expenditure | -3.59 | Change in Zk | NS | Difference between impact after 24 months and impact after 36 months | | 2 | Angelucci et al. (2012) | Oportunidades (Mexico) | Total monthly household expenditure | 5.82 | Change in pesos | 1% | After 1 year | | | | Oportunidades (Mexico) | Total monthly household expenditure | 5.49 | Change in pesos | 5% | After 2 years | | | | Oportunidades (Mexico) | Total monthly food expenditure | 168.54 | Change in pesos | 10% | After 1 year | | | | Oportunidades (Mexico) | Total monthly food expenditure | 282.85 | Change in pesos | 1% | After 2 years | | 3 | Buser et al. (2014) | BDH (Ecuador) | Monthly food expenditure | 16.383 | Change in USD | NS | Stopped receiving the transfer two years ago | | 4 | Gertler et al. (2012) | Oportunidades (Mexico) | Household per capita consumption | 10.836 | Change in pesos | 5% | Compared to households that joined 4 years later | | 5 | Maluccio & Flores (2005) | RPS (Nicaragua) | Nominal annual total per capita expenditure | 986 | Change in Cordobas | 1% | After 1 year | | | | RPS (Nicaragua) | Nominal annual total per capita expenditure | 686 | Change in Cordobas | 1% | After 2 years | | | | RPS (Nicaragua) | Nominal annual food per capita expenditure | 871 | Change in Cordobas | 1% | After 1 year | | | | RPS (Nicaragua) | Nominal annual food per capita expenditure | 640 | Change in Cordobas | 1% | After 2 years |

Continued on next page

### A5.1.2 Summary of results for the role of cash transfer design and implementation parameters on monetary poverty continued

| # | Study | Programme | Indicator | Effect | Measure of change | Significance | Additional details | |----|------------------------|--------------------|-----------------------------------------------|--------|-------------------|--------------|--------------------| | 6 | Maluccio (2010) | RPS (Nicaragua) | Per capital annual total expenditure | 905 | Change in Cordobas| 1% | After 1 year | | | | RPS (Nicaragua) | Per capital annual total expenditure | 676 | Change in Cordobas| 5% | After 2 years | | | | RPS (Nicaragua) | Per capital annual food expenditure | 789 | Change in Cordobas| 1% | After 1 year | | | | RPS (Nicaragua) | Per capital annual food expenditure | 621 | Change in Cordobas| 1% | After 2 years | | 7 | Miller et al. (2011) | SCTP (Malawi) | Weekly per capita total expenditures | 254 | Change in MK | 1% | After 6 months | | | | SCTP (Malawi) | Weekly per capita total expenditures | 274 | Change in MK | 1% | After 1 year | | | | SCTP (Malawi) | Weekly per capita food expenditures | 198 | Change in MK | 1% | After 6 months | | | | SCTP (Malawi) | Weekly per capita food expenditures | 203 | Change in MK | 1% | After 1 year | | 8 | Perova & Vakis (2012) | Juntos (Peru) | Overall consumption (in log?) | 0.09 | Percentage point change | 1% | 12 to 23 months in Juntos | | | | Juntos (Peru) | Overall consumption (in log?) | 0.11 | Percentage point change | 1% | 24 to 36 months in Juntos | | | | Juntos (Peru) | Overall consumption (in log?) | 0.15 | Percentage point change | 5% | Over 36 months in Juntos | | | | Juntos (Peru) | Overall food consumption (in log?) | 0.09 | Percentage point change | 1% | 12 to 23 months in Juntos | | | | Juntos (Peru) | Overall food consumption (in log?) | 0.1 | Percentage point change | 5% | 24 to 36 months in Juntos | | | | Juntos (Peru) | Overall food consumption (in log?) | 0.13 | Percentage point change | 10% | Over 36 months in Juntos | | | | Juntos (Peru) | Poverty head count | -0.08 | Percentage point change | 1% | 12 to 23 months in Juntos | | | | Juntos (Peru) | Poverty head count | -0.1 | Percentage point change | 10% | 24 to 36 months in Juntos | | | | Juntos (Peru) | Poverty head count | -0.1 | Percentage point change | 10% | Over 36 months in Juntos | | | | Juntos (Peru) | Poverty gap | -4.8 | Percentage point change | 10% | 12 to 23 months in Juntos | | | | Juntos (Peru) | Poverty gap | -3.8 | Percentage point change | NS | 24 to 36 months in Juntos | | | | Juntos (Peru) | Poverty gap | -0.61 | Percentage point change | NS | Over 36 months in Juntos | | 9 | Skoufias & Di Maro (2008) | PROGRESA (Mexico) | Poverty head count | 0.0007 | Percentage point change | NS | After 6 months | | | | PROGRESA (Mexico) | Poverty head count | -0.06 | Percentage point change | NS | After 1 year | | | | PROGRESA (Mexico) | Poverty head count | -0.0207| Percentage point change | 5% | After 1.5 years | | | | PROGRESA (Mexico) | Poverty gap (not clear how measured) | -0.0284| ? | 1% | After 6 months | | | | PROGRESA (Mexico) | Poverty gap (not clear how measured) | -0.0445| ? | 1% | After 1 year | | | | PROGRESA (Mexico) | Poverty gap (not clear how measured) | -0.0794| ? | 1% | After 1.5 years |

**Targeting mechanism**

| # | Study | Programme | Indicator | Effect | Measure of change | Significance | Additional details | |----|------------------------|--------------------|-----------------------------------------------|--------|-------------------|--------------|--------------------| | 1 | Merttens et al. (2015) | SAGE (Uganda) | Monthly total expenditure per equivalent adult | 10,000 | Change in UGX | 10% | SGC | | | | SAGE (Uganda) | Monthly total expenditure per equivalent adult | 11,000 | Change in UGX | 10% | VFSG | | | | SAGE (Uganda) | Monthly food expenditure per equivalent adult | 1500 | Change in UGX | NS | SGC | | | | SAGE (Uganda) | Monthly food expenditure per equivalent adult | 8500 | Change in UGX | 5% | VFSG |

*Continued on next page*

### A5.1.2 Summary of results for the role of cash transfer design and implementation parameters on monetary poverty continued

| # | Study | Programme | Indicator | Effect | Measure of change | Significance | Additional details | |----|--------------------------------------------|----------------------------|-----------------------------------------------|--------|-------------------|--------------|-----------------------------------------------------------------------------------| | 1 | Blattman et al. (2015) | WINGS (Uganda) | Household monthly non-durable expenditure | 31.031 | Change in 1000s of UGX | 1% | Effect of those that received no training compared to non-beneficiaries | | | | | Household monthly non-durable expenditure | 33.439 | Change in 1000s of UGX | 1% | Effect of those that received training compared to non-beneficiaries | | | | | Household monthly non-durable expenditure | -1.008 | Change in 1000s of UGX | NS | Effect of those that had 2 supervision visits compared to no supervision | | | | | Household monthly non-durable expenditure | -3.022 | Change in 1000s of UGX | NS | Effect of those that had 5 supervision visits compared to no supervision | | 2 | Green et al. (2015) | WINGS (Uganda) | Individual monthly non-durable consumption | -0.06 | Z-score | NS | For female beneficiaries who attended training alone, compared to Phase 1 beneficiaries | | | | | Individual monthly non-durable consumption | -0.28 | Z-score | 1% | For female beneficiaries who attended training alone, compared to Phase 1 beneficiaries | | 3 | Karlan et al. (2014) | IPA RCT (Ghana) | Total expenditure in 12 months | 2.44 | Change in USD | NS | For beneficiaries receiving both cash and insurance | | 4 | Macours and Vakis (2012) | Atención a Crisis (Nicaragua) | Log total per capita expenditure | 0.281 | Change in log points | 1% | For the basic transfer (after less than 1 year) | | | | Atención a Crisis (Nicaragua) | Log total per capita expenditure | 0.285 | Change in log points | 1% | The basic CCT plus a scholarship for a vocational training (after less than 1 year) | | | | Atención a Crisis (Nicaragua) | Log total per capita expenditure | 0.331 | Change in log points | 1% | The basic CCT plus a productive investment grant (after less than 1 year) | | | | Atención a Crisis (Nicaragua) | Log total per capita expenditure | 0.022 | Change in log points | NS | For the basic transfer (after 2 years) | | | | Atención a Crisis (Nicaragua) | Log total per capita expenditure | 0.048 | Change in log points | NS | The basic CCT plus a scholarship for a vocational training (after 2 years) | | | | Atención a Crisis (Nicaragua) | Log total per capita expenditure | 0.088 | Change in log points | 1% | The basic CCT plus a productive investment grant (after 2 years) | | 5 | Macours, Premand and Vakis (2012) | Atención a Crisis (Nicaragua) | Log total household per capita | 0.0221 | Percentage change | NS | For the basic transfer | | | | Atención a Crisis (Nicaragua) | Log total household per capita | 0.0277 | Percentage change | NS | The basic CCT plus a scholarship for a vocational training | | | | Atención a Crisis (Nicaragua) | Log total household per capita | 0.0837 | Percentage change | 1% | The basic CCT plus a productive investment grant | | | | Atención a Crisis (Nicaragua) | Log food household per capita | 0.0449 | Percentage change | 1% | For the basic transfer | | | | Atención a Crisis (Nicaragua) | Log food household per capita | 0.0488 | Percentage change | 5% | The basic CCT plus a scholarship for a vocational training | | | | Atención a Crisis (Nicaragua) | Log food household per capita | 0.102 | Percentage change | 1% | The basic CCT plus a productive investment grant |

### Summary tables results for Education

#### Table A5.2.1 Summary of results for cash transfer effects disaggregated by gender for education indicators

| # | Study | Programme (Country) | Variable and treatment population (e.g. age of child) | Effect | Measure of change | Significance | Details/explanation | |----|------------------------|---------------------|-------------------------------------------------------|--------|------------------|--------------|--------------------| | 1 | Akresh et al. (2013) | NCTPP (Burkina Faso)| Percentage of school days the child attended during the entire academic year (school roster) | 0.135 | Percentage | 1% | CCT, aged 7-15, Male | | | | NCTPP (Burkina Faso)| Percentage of school days the child attended during the entire academic year (school roster) | 0.137 | Percentage | 1% | CCT, aged 7-15, Female | | | | NCTPP (Burkina Faso)| Percentage of school days the child attended during the entire academic year (school roster) | 0.108 | Percentage | 5% | UCT, aged 7-15, Male | | | | NCTPP (Burkina Faso)| Percentage of school days the child attended during the entire academic year (school roster) | 0.032 | Percentage | NS | UCT, aged 7-15, Female | | 2 | Baird et al. (2011) | ZCTP (Malawi) | Percentage of days respondent enrolled in school was recorded present during the days the school was in session (school ledger) | 0.08 | Fraction of days | 5% | CCT, Overall effect (all terms in 2009) girls only | | | | ZCTP (Malawi) | Percentage of days respondent enrolled in school was recorded present during the days the school was in session (school ledger) | 0.058 | Fraction of days | NS | UCT, Overall effect (all terms in 2009) girls only | | 3 | Bentassine et al. (2013)| Tayssir (Morocco) | Attendance rate during surprise school visits among those enrolled (School visits) | 0.069 | Percentage | 1% | Labelled CT, after 2 years, administered to one child per household aged 6-12, Male | | | | Tayssir (Morocco) | Attendance rate during surprise school visits among those enrolled (School visits) | 0.082 | Percentage | 1% | Labelled CT, after 2 years, administered to one child per household aged 6-12, Female | | | | Tayssir (Morocco) | Attending School by end of year 2, among those 6-15 at baseline (Household survey) | 0.007 | Percentage | NS | Labelled CT, after 2 years, administered to one child per household aged 6-12, Male | | | | Tayssir (Morocco) | Attending School by end of year 2, among those 6-15 at baseline (Household survey) | 0.006 | Percentage | NS | Labelled CT, after 2 years, administered to one child per household aged 6-12, Female | | 4 | Dammert et al. (2009) | RPS (Nicaragua) | School attendance | 0.110 | Percentage | 5% | CCT, children aged 7-13 years at baseline, after two years, Girls | | | | RPS (Nicaragua) | School attendance | 0.173 | Percentage | 5% | CCT, children aged 7-13 years at baseline, after 2 years, Boys | | 5 | De Groot et al. (2015) | LEAP (Ghana) | whether a child missed any days of school in the reference period | -0.13 | Percentage | 1% | CCT, aged 5-12, Male | | | | LEAP (Ghana) | whether a child missed any days of school in the reference period | -0.083 | Percentage | 5% | CCT, aged 5-12, Female | | | | LEAP (Ghana) | whether a child missed any days of school in the reference period | 0.004 | Percentage | NS | CCT, aged 13-17, Male | | | | LEAP (Ghana) | whether a child missed any days of school in the reference period | -0.098 | Percentage | 10% | CCT, aged 13-17, Female | | 6 | Evans et al. (2014) | TSAF (Tanzania) | Ever attended school | 0 | Percentage | NS | CCT, children aged 0-18 years, after 31-34 months, Male | | | | TSAF (Tanzania) | Ever attended school | 0.05 | Percentage | 10% | CCT, children aged 0-18 years, after 31-34 months, Female | | | | TSAF (Tanzania) | Missed school last week if enrolled due to personal reasons (Absenteeism) | 0.02 | Percentage | NS | CCT, children aged 0-18 years, after 31-34 months, Male | | | | TSAF (Tanzania) | Missed school last week if enrolled due to personal reasons (Absenteeism) | 0.01 | Percentage | NS | CCT, children aged 0-18 years, after 31-34 months, Female | | | | TSAF (Tanzania) | Took national exam-Standard IV+ | 0.01 | Percentage | NS | CCT, children aged 0-18 years, after 31-34 months, Male | | | | TSAF (Tanzania) | Took national exam-Standard IV+ | 0.04 | Percentage | NS | CCT, children aged 0-18 years, after 31-34 months, Female |

*continued on next page*

### Table A5.2.1 Summary of results for cash transfer effects disaggregated by gender for education indicators continued

| # | Study | Programme | Variable and treatment population (e.g. age of child) | Effect | Measure of change | Significance | Details/explanation | |----|--------------------------------------------|----------------------------|----------------------------------------------------------------------------------------------------------------------|--------|-------------------|--------------|-------------------------------------------------------------------------------------| | 7 | Filmer et al. (2008) | JFPR (Cambodia) | Attendance on the day of school visit | 0.319 | Percentage | 1% | CCT, effect on girls only | | 8 | Handa et al. (2014) | LEAP (Ghana) | Whether a child missed any days of school in the reference period (Absenteism) | -0.11 | Percentage | 10% | UCT, girls aged 13-17 | | | | | whether a child did not attend any school in the last week (Absenteism) | -0.11 | Percentage | NS | UCT, girls aged 13-17 | | 9 | Lincove et al. (2014) | RPS (Nicaragua) | Whether child attended school (at time of survey) | 0.125 | Percentage | 1% | CCT, Children aged 6-11 at baseline (always eligible), Male | | | | | Whether child attended school (at time of survey) | 0.158 | Percentage | 5% | CCT, Children aged 6-11 at baseline (always eligible), Female | | 10 | Maluccio and Flores (2005) | RPS (Nicaragua) | Current attendance (child was defined to be currently attending if he indicated he was still enrolled and had either missed 3 or fewer days in the past month (or more because of illness) | 0.23 | Percentage | 10% | CCT, after two years, Boys aged 7-13 who had not completed fourth grade | | | | | Current attendance (child was defined to be currently attending if he indicated he was still enrolled and had either missed 3 or fewer days in the past month (or more because of illness) | 0.17 | Percentage | 10% | CCT, after two years, Girls aged 7-13 who had not completed fourth grade | | 11 | Merttens et al. (2013) | HSNP (Kenya) | Proportion of children currently attending school | -0.0661| Percentage | NS | UCT, after three years, children aged 6-17, Male | | | | | Proportion of children currently attending school | -0.059 | Percentage | NS | UCT, after three years, children aged 6-17, Female | | 12 | Merttens et al. (2015) | SAGE Senior Citizen Grant (Uganda) | Proportion of children currently attending formal education | -0.012 | Percentage Points | NS | Children aged 6-17, after one year, Male | | | | | Proportion of children currently attending formal education | 0.0037 | Percentage Points | NS | Children aged 6-17, after one year, Female | | | | | Proportion of children currently attending formal education | -0.006 | Percentage Points | NS | Children aged 6-17, after one year, Male | | | | | Proportion of children currently attending formal education | -0.061 | Percentage Points | 10% | Children aged 6-17, after one year, Female | | | | | Mean number of days missed in last 30 scheduled school days (absenteeism) | -0.36 | Mean number of days missed in last 30 scheduled days | NS | Children aged 6-17, after one year, Male | | | | | Mean number of days missed in last 30 scheduled school days (absenteeism) | -13.600| Mean number of days missed in last 30 scheduled days | NS | Children aged 6-17, after one year, Female | | | | | Mean number of days missed in last 30 scheduled school days (absenteeism) | -0.81 | Mean number of days missed in last 30 scheduled days | NS | Children aged 6-17, after one year, Male | | | | | Mean number of days missed in last 30 scheduled school days (absenteeism) | 0.44 | Mean number of days missed in last 30 scheduled days | NS | Children aged 6-17, after one year, Female |

continued on next page Table A5.2.1 Summary of results for cash transfer effects disaggregated by gender for education indicators

| # | Study | Programme (Country) | Variable and treatment population (e.g. age of child) | Effect | Measure of change | Significance | Details/explanation | |----|------------------------|---------------------|------------------------------------------------------|--------|-------------------|--------------|---------------------| | 13 | Miller et al. (2011) | SCTP (Malawi) | No of days absent per month | -1.2 | Days absent per month | NS | UCT, aged 6-8, Boys | | | | | | | | | | | | | | | 0.2 | Days absent per month | NS | UCT, aged 9-11, Boys | | | | | | -1.9 | Days absent per month | 5% | UCT, aged 12-15, Boys | | | | | | 0.3 | Days absent per month | NS | UCT, aged 16-18, Boys | | | | | | -1.8 | Days absent per month | 5% | UCT, aged 6-8, Girls | | | | | | -1.2 | Days absent per month | 10% | UCT, aged 9-11, Girls | | | | | | 0.1 | Days absent per month | NS | UCT, aged 12-15, Girls | | | | | | -2 | Days absent per month | 10% | UCT, aged 16-18 Girls | | 14 | Pellerano et al. (2014)| LCGP (Lesotho) | Proportion of pupils 6-19 who missed school in the 30 days prior to the survey – self-reported (absenteeism) | 0.01497 | Percentage | NS | UCT, after two years, children aged 6-19, Male | | | | | | 0.00661 | Percentage | NS | UCT, after two years, children aged 6-19, Female | | 15 | Skoufias and Parker (2001)| PROGRESA (Mexico) | Probability of attending school | 0.018 | Percentage | 1% | CCT, Nov-99 FU, 8-11 years, Boys | | | | | | -0.003 | Percentage | NS | CCT, Nov-99 FU, 8-11 years, Girls | | | | | | 0.058 | Percentage | 1% | CCT, Nov-99 FU, 12-17 years, Boys | | | | | | 0.095 | Percentage | 1% | CCT, Nov-99 FU, 12-17 years, Girls |

Attendance (Household Head)

| # | Study | Programme (Country) | Variable and treatment population (e.g. age of child) | Effect | Measure of change | Significance | Details/explanation | |----|------------------------|---------------------|------------------------------------------------------|--------|-------------------|--------------|---------------------| | 1 | Dammert et al. (2009) | RPS (Nicaragua) | School attendance | 0.172 | Percentage | 5% | CCT, children aged 7-13 years at baseline, after 2 years Household Head is Female | | | | | | 0.138 | Percentage | 5% | CCT, children aged 7-13 years at baseline, after 2 years, Household Head is Male | | 2 | World Bank (2011) | PKH (Indonesia) | Regular primary school attendance (>85%) | 0.01 | Percentage point | NS | CCT, children aged 7-12, Household Head is Male | | | | | Hours in school last week | -0.02 | Percentage point | NS | CCT, children aged 7-12, Household Head is Female | | | | | Hours in school last week | 0.369 | Hours spent in school last week | 10% | CCT, children aged 7-12, Household Head is Male | | | | | Hours in school last week | -0.107 | Hours spent in school last week | NS | CCT, children aged 7-12, Household Head is Female | | | | | Regular junior secondary school attendance (>85%) | 0.016 | Percentage point | NS | CCT, children aged 13-15, Household Head is Male | | | | | Regular junior secondary school attendance (>85%) | -0.003 | Percentage point | NS | CCT, children aged 13-15, Household Head is Female | | | | | Hours in school last week | 0.699 | Hours spent in school last week | 5% | CCT, children aged 13-15, Household Head is Male | | | | | Hours in school last week | 0.393 | Hours spent in school last week | NS | CCT, children aged 13-15, Household Head is Female |

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### Table A5.2.1 Summary of results for cash transfer effects disaggregated by gender for education indicators continued

| # | Study | Programme | Variable and treatment population (e.g. age of child) | Effect | Measure of change | Significance | Details/explanation | |---|---|---|---|---|---|---|---| | **Math Test Scores** | | | | | | | | | 1 | Baez et al. (2011) | Familias en Accion (Colombia) | Standardized math test score (Icfes test) | 0.025 | Change in Standard deviation | NS | CCT, Boys | | | | Familias en Accion (Colombia) | Standardized math test score (Icfes test) | -0.045 | Change in Standard deviation | NS | CCT, Girls | | 2 | Baird et al. (2011) | ZCTP (Malawi) | Standardized math test score (TIMMS) | 0.006 | Change in Standard deviation | NS | UCT, after 2 years, 13-22 years, Girls | | | | ZCTP (Malawi) | Standardized math test score (TIMMS) | 0.12 | Change in Standard deviation | 10% | CCT, after 2 years, 13-22 years, Girls | | | | ZCTP (Malawi) | Standardized math test score (Non-TIMMS) | 0.063 | Change in Standard deviation | NS | UCT, after 2 years, 13-22 years, Girls | | | | ZCTP (Malawi) | Standardized math test score (Non-TIMMS) | 0.086 | Change in Standard deviation | NS | CCT, after 2 years, 13-22 years, Girls | | 3 | Baird et al. (2013) | ZCTP (Malawi) | Standardized mathematics test score | 0.164 | Change in Score | 5% | CCT, after 2 years, 13-22 years, Girls (baseline dropout) | | 4 | Benhassine et al. (2013) | Tayssir (Morocco) | Basic Arithmetic test – Summary Index (Based on ASER test developed by Pratham) | 0.091 | Change in Score | NS | Labeled CT to fathers, after 2 years, administered to one child per household aged 6-12, Boys | | | | Tayssir (Morocco) | Basic Arithmetic test – Summary Index (Based on ASER test developed by Pratham) | 0.082 | Change in Score | NS | Labeled CT to fathers, after 2 years, administered to one child per household aged 6-12, Girls | | **Language Test Scores** | | | | | | | | | 1 | Baez et al. (2011) | Familias en Accion (Colombia) | Spanish test score (Icfes test) | -0.057 | Change in Standard deviation | NS | CCT Boys | | | | Familias en Accion (Colombia) | Spanish test score (Icfes test) | -0.034 | Change in Standard deviation | NS | CCT Girls | | 2 | Baird et al. (2011) | ZCTP (Malawi) | English Reading Comprehension Test Score (standardized) | 0.14 | Change in Standard Deviation | 1% | CCT, after 2 years, 13-22 years, Girls | | | | ZCTP (Malawi) | English Reading Comprehension Test Score (standardized) | -0.030 | Change in Standard Deviation | NS | UCT, after 2 years, 13-22 years, Girls | | 3 | Baird et al. (2013) | ZCTP (Malawi) | English Reading Comprehension test score (standardized) | 0.131 | Change in Standard deviation | 10% | CCT, after 2 years, 13-22 years, Girls, (baseline dropout) | | 4 | Evans et al. (2014) | TSAF (Tanzania) | Literate (self-reported) | 0 | Change in Percentage | NS | CCT, children aged 0-18 years, after 31-34 months, Boys | | | | TSAF (Tanzania) | Literate (self-reported) | 0.2 | Change in Percentage | NS | CCT, children aged 0-18 years, after 31-34 months, Girls | | **Composite Test Score** | | | | | | | | | 1 | Baez et al. (2011) | Familias en Accion (Colombia) | Composite test score in various subjects (Icfes test) | -0.015 | Change in Standard Deviation | NS | CCT, Boys | | | | Familias en Accion (Colombia) | Composite test score in various subjects (Icfes test) | -0.028 | Change in Standard Deviation | NS | CCT, Girls | | **Cognitive Development** | | | | | | | | | 1 | Baird et al. (2011) | ZCTP (Malawi) | Cognitive test score (standardized), version of Raven’s Colored Progressive Matrices that was used in the Indonesia Family Life Survey (IFLS-2) | 0.174 | Change in Standard Deviation | 1% | CCT, after 2 years, 13-22 years, Girls | | | | ZCTP (Malawi) | Cognitive test score (standardized), version of Raven’s Colored Progressive Matrices that was used in the Indonesia Family Life Survey (IFLS-2) | 0.136 | Change in Standard Deviation | NS | UCT, after 2 years, 13-22 years, Girls |

*continued on next page* Table A5.2.1 Summary of results for cash transfer effects disaggregated by gender for education indicators continued

| # | Study | Programme | Variable and treatment population (e.g., age of child) | Effect | Measure of change | Significance | Details/explanation | |----|------------------------|----------------------------|--------------------------------------------------------|--------|-------------------|--------------|---------------------| | 2 | Baird et al. (2013) | ZCTP (Malawi) | Cognitive test score (standardized), version of Raven’s Colored Progressive Matrices that was used in the Indonesia Family Life Survey (FLS-2) | 0.142 | Change in Standard deviation | 5% | CCT, after 2 years, 13-22 years, Girls, (baseline dropout) | | 3 | Gertler and Fernald (2004) | PROGRESA / Oportunidades (Mexico) | Log Long Term Memory test score | 4.87 | Change in score over control | NS | CCT, 3-6 years, effect on boys only | | | | | Log Short Term Memory test score | 3.32 | Change in score over control | NS | CCT, 3-6 years, effect on boys only | | | | | Log Visual Integration test score | 3.76 | Change in score over control | NS | CCT, 3-6 years, effect on boys only | | | | | Log Peabody Picture Vocabulary test score | 4.88 | Change in score over control | NS | CCT, 3-6 years, effect on boys only | | | | | Communication Dev. Inventory | 5.73 | Change in score over control | NS | CCT, 3-6 years, effect on boys only | | | | | Sentences test score | 6.78 | Change in score over control | 5% | CCT, 3-6 years, effect on boys only | | | | | Log Long Term Memory test score | -3.83 | Change in score over control | NS | CCT, 3-6 years, effect on girls only | | | | | Log Short Term Memory test score | 5.24 | Change in score over control | NS | CCT, 3-6 years, effect on girls only | | | | | Log Visual Integration test score | -3.63 | Change in score over control | NS | CCT, 3-6 years, effect on girls only | | | | | Log Peabody Picture Vocabulary test score | -3.55 | Change in score over control | NS | CCT, 3-6 years, effect on girls only | | | | | Communication Dev. Inventory | 5.58 | Change in score over control | NS | CCT, 3-6 years, effect on girls only | | | | | Sentences test score | 8.82 | Change in score over control | NS | CCT, 3-6 years, effect on girls only | | 4 | Paxson & Schady (2010) | BDH (Ecuador) | Cognitive and behavioural combined index (includes scores on the TVP test and three tests from the Woodcock-Johnson-Mönzö battery assessment) | 0.241 | Change in standard deviation | 5% | CCT, effects on girls only, between 12 and 18 months after the beginning of the programme, aged 3-7 years | | | | | Cognitive and behavioural combined index (includes scores on the TVP test and three tests from the Woodcock-Johnson-Mönzö battery assessment) | 0.115 | Change in standard deviation | NS | CCT, effects on boys only, between 12 and 18 months after the beginning of the programme, aged 3-7 years |

1. Unit of observation are children (enrolled or not in school) who were 18 or below when they joined the program and that, based on their school attainment at the pre-program time, could have achieved grade 11 between 2003 and 2009, and the number of years needed to complete high school was lower than the number of years of treatment.

2. This exam is a nationally recognized and standardized test that is administered prior to graduation from high school and mandatory for entrance to higher education (Baez et al. 2011, p. 13)

3. Unit of observation are children (enrolled or not in school) who were 18 or below when they joined the program and that, based on their school attainment at the pre-program time, could have achieved grade 11 between 2003 and 2009, and the number of years needed to complete high school was lower than the number of years of treatment.

4. This exam is a nationally recognized and standardized test that is administered prior to graduation from high school and mandatory for entrance to higher education (Baez et al. 2011, p. 13)

5. TIMMS stands for Trends in Mathematics and Science Study, which is a cycle of internationally comparative assessments in mathematics and science carried out at the fourth and eighth grades every 4 years. Authors also borrowed five mathematics questions from the 2007 TIMMS and incorporated them into an independently developed mathematics test (Non-TIMMS). 6 Unit of observation are children (enrolled or not in school) who were 18 or below when they joined the program and that, based on their school attainment at the pre-program time, could have achieved grade 11 between 2003 and 2009, and the number of years needed to complete high school was lower than the number of years of treatment.

7 Unit of observation are children (enrolled or not in school) who were 18 or below when they joined the program and that, based on their school attainment at the pre-program time, could have achieved grade 11 between 2003 and 2009, and the number of years needed to complete high school was lower than the number of years of treatment.

8 Overall scores of Icfes test The exam is a standardized test that assesses the academic achievement of students in various subjects such as Mathematics, Language, Biology, Chemistry, Physics, History, Geography (Baez et al. 2011, p. 14)

### Table A5.2.2 Summary of results for the role of cash transfer design and implementation parameters on education

| # | Study and country | Design / Implementation Parameter | Variable | Effect Measure of change | Significance Details/ explanation | |----|-------------------|-----------------------------------|----------|--------------------------|-----------------------------------| | **School Attendance** | | | | | | | 1 | Akresh et al. (2013) | NCTPP (Burkina Faso) | Conditionality | Attendance (School Roster Report), all children 7-15 | 0.134 Percentage 1% CCT round 3 | | | | NCTPP (Burkina Faso) | Conditionality | Attendance (School Roster Report), all children 7-15 | 0.067 Percentage NS UCT round 3 | | 2 | Baird et al. (2011) | ZCTP (Malawi) | Conditionality | Fraction of days respondent attended school (School ledgers) | 0.080 Percentage 5% Term 1-3 2009, CCT | | | | ZCTP (Malawi) | Conditionality | Fraction of days respondent attended school (School ledgers) | 0.058 Percentage NS Term 1-3 2009, UCT | | 3 | Barrera-Osorio et al. (2008) | SCAE (Colombia) | Frequency of Payment | Verified attendance at school | 0.033 Percentage 1% Effect of Basic CCT only, San Cristobal District | | | | SCAE (Colombia) | Frequency of Payment | Verified attendance at school | 0.028 Percentage 1% Effect of a savings CCT, where 2/3 transfer given immediately and 1/3 given at enrolment, San Cristobal District | | | | SCAE (Colombia) | Conditionality | Verified attendance at school | 0.009 Percentage NS Effect of Basic CCT only, Suba District, grades 6-8 | | | | SCAE (Colombia) | Conditionality | Verified attendance at school | 0.05 Percentage 1% Effect of transfers conditional on graduation and tertiary enrolment rather than attendance, Suba, grades 9-11 | | 4 | Benhassine et al. (2013) | Tayssir (Morocco) | Main Recipient | Attendance rate during surprise school visits (School sample, children 6-12) | 0.002 Percentage NS After 2 years, difference between LCT to mothers and LCT to fathers | | | | Tayssir (Morocco) | Main Recipient | Attending school by end of year 2, among those 6-15 at baseline (household sample) | 0.004 Percentage NS After 2 years, difference between LCT to mothers and LCT to fathers | | | | Tayssir (Morocco) | Main Recipient | Attendance rate during surprise school visits (School sample, children 6-12) | 0.918 P value NS P-value for Mother different from Father | | | | Tayssir (Morocco) | Main Recipient | Attending school by end of year 2, among those 6-15 at baseline (household sample) | 0.962 P value NS P-value for Mother different from Father | | | | Tayssir (Morocco) | Conditionality | Attendance rate during surprise school visits (School sample, children 6-12) | 0.007 Percentage NS After 2 years, difference between CCT to fathers and LCT to fathers | | | | Tayssir (Morocco) | Conditionality | Attending school by end of year 2, among those 6-15 at baseline | -0.019 Percentage NS After 2 years, difference between CCT to fathers and LCT to fathers | | | | Tayssir (Morocco) | Conditionality | Attending school by end of year 2, among those 6-15 at baseline | 0.01 P value 1% P-value for CCT different from LCT | | | | Tayssir (Morocco) | Conditionality | Attendance rate during surprise school visits (School sample, children 6-12) | 0.125 P value NS P-value for CCT different from LCT | | 5 | Filmer and Schady (2011) | CSP (Cambodia) | Transfer Level | child’s presence at school during unannounced visit (Secondary School students) | 0.023 Percentage NS Pooled estimate across four visits, $60 scholarship compared to those who were offered a $45 scholarship |

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### Table A5.2.2 Summary of results for the role of cash transfer design and implementation parameters on education continued

| # | Study and country | Programme and country | Design / Implementation Parameter | Variable | Effect | Measure of change | Significance | Details/ explanation | |----|-------------------|-----------------------|-----------------------------------|----------|--------|-------------------|--------------|---------------------| | 6 | Macours and Vakis (2009) | Atencion a Crisis (Nicaragua) | Complementary Programme | Attending school (children aged 7-18) | 0.057 | Percentage | 5% | After 9 months, Basic CCT only | | | | Atencion a Crisis (Nicaragua) | Complementary Programme | Number of days absent from school (absenteeism, children aged 7-18) | -1.574 | Percentage | 1% | After 9 months, Basic CCT only | | | | Atencion a Crisis (Nicaragua) | Complementary Programme | Attending school | 0.045 | Percentage | 5% | After 9 months, Basic CCT plus grant for productive investments | | | | Atencion a Crisis (Nicaragua) | Complementary Programme | Number of days absent from school (absenteeism) | -1.107 | Percentage | 5% | After 9 months, Basic CCT plus grant for productive investments | | | | Atencion a Crisis (Nicaragua) | Complementary Programme | Attending school | 0.049 | Percentage | 5% | After 9 months, Basic CCT plus scholarship for occupational training | | | | Atencion a Crisis (Nicaragua) | Complementary Programme | Number of days absent from school (absenteeism) | -1.438 | Percentage | 1% | After 9 months, Basic CCT plus scholarship for occupational training | | 7 | Mortens et al. (2015) | SAGE (Uganda) | Targeting | Proportion of children 6-17 currently attending formal education | -0.0043 | Percentage point | NS | Among households targeted through the Senior Citizens Grant | | | SAGE (Uganda) | Targeting | Proportion of children 6-17 currently attending formal education | -0.034 | Percentage point | 10% | Among households targeted through the Vulnerable Family Support Grant | | | SAGE (Uganda) | Targeting | Proportion of boys 6-17 currently attending formal education | -0.012 | Percentage point | NS | Among households targeted through the Senior Citizens Grant | | | SAGE (Uganda) | Targeting | Proportion of boys 6-17 currently attending formal education | -0.0006 | Percentage point | NS | Among households targeted through the Vulnerable Family Support Grant | | | SAGE (Uganda) | Targeting | Proportion of girls 6-17 currently attending formal education | 0.0037 | Percentage point | NS | Among households targeted through the Senior Citizens Grant | | | SAGE (Uganda) | Targeting | Proportion of girls 6-17 currently attending formal education | -0.061 | Percentage point | 10% | Among households targeted through the Vulnerable Family Support Grant | | | SAGE (Uganda) | Targeting | Mean number of days missed in last 30 scheduled school days (absenteeism) | 0.14 | Percentage point | NS | Among households targeted through the Senior Citizens Grant | | | SAGE (Uganda) | Targeting | Mean number of days missed in last 30 scheduled school days (absenteeism) | -0.36 | Percentage point | NS | Among households targeted through the Vulnerable Family Support Grant | | 8 | Penova and Vakis (2012) | Juntos (Peru) | Duration of exposure | Currently attending school, conditional on registration (children aged 6-14) | 0.01 | Percentage | NS | Being a beneficiary for over 12-23 months (compared to less than one year) | | | Juntos (Peru) | Duration of exposure | Currently attending school, conditional on registration | 0.03 | Percentage | 1% | Being a beneficiary for over 24-26 months (compared to less than a year) | | | Juntos (Peru) | Duration of exposure | currently attending school, conditional on registration | 0.01 | Percentage | NS | Being a beneficiary for over 36 months (compared to less than a year) | | 9 | Villa (2014) | Familias en accion (Colombia) | Duration of exposure | Years of education (among those enrolled at 7 years old) | 4.4 | Years of difference between least and most exposed | 1% | Difference between households with highest and lowest proportion of potential exposure |

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### Table A5.2.2 Summary of results for the role of cash transfer design and implementation parameters on education continued

| # | Study | Programme and country | Design / Implementation Parameter | Variable | Effect Measure of change | Significance | Details/ explanation | |----|-------|-----------------------|-----------------------------------|----------|--------------------------|-------------|---------------------| | 1 | Baird et al. (2011) | ZCTP (Malawi) | Conditionality | English Reading Comprehension Test Score (standardized) | 0.14 Standard Deviation | 1% | CCT, after 2 years, Girls aged 13-22 | | | | | | English Reading Comprehension Test Score (standardized) | -0.030 Standard Deviation | NS | UCT, after 2 years, Girls aged 13-22 | | | | | | English Reading Comprehension Test Score (standardized) | -0.032 Standard Deviation | NS | After 2 years, 13-22 years, Girls, CCT individual amount | | | | | | English Reading Comprehension Test Score (standardized) | -0.019 Standard Deviation | NS | After 2 years, 13-22 years, Girls, UCT individual amount | | | | | | English Reading Comprehension Test Score (standardized) | 0 Standard Deviation | NS | After 2 years, 13-22 years, Girls, CCT household amount | | | | | | English Reading Comprehension Test Score (standardized) | -0.058 Standard Deviation | 5% | After 2 years, 13-22 years, Girls, UCT household amount | | 2 | Behrman et al. (2009) | PROGRESA / Oportunidades (Mexico) | Duration of Exposure | Reading skills (Woodcock Johnson test) | -0.11 Percentage | NS | Extra 18 months of the programme, Female aged 9-15 in 1997 | | | | | | Reading skills (Woodcock Johnson test) | 0.199 Percentage | NS | Extra 18 months of the programme Male, aged 9-15 in 1997 | | | | | | Written Language (Woodcock Johnson test) | -0.301 Percentage | NS | Extra 18 months of the programme, Female aged 9-15 in 1997 | | | | | | Written Language (Woodcock Johnson test) | -0.011 Percentage | NS | Extra 18 months of the programme, Male, aged 9-15 in 1997 | | 3 | Evans et al. (2014) | TSAF (Tanzania) | Duration of Exposure | Literate (self-reported) | 0.04 Percentage | 10% | CCT, children aged 0-18 years, after 18-21 months | | | | | | Literate (self-reported) | 0.02 Percentage | NS | CCT, children aged 0-18 years, after 31-34 months | | 4 | Fernald et al. (2008) | Oportunidades (Mexico) | Cumulative cash transfer (duration & transfer size) | Peabody score | 0.18 Log of raw score | 1% | Effect of doubling cumulative cash transfers from median of 7500 to 15000 pesos on children 36-68 months old |

### Math Test Scores

| # | Study | Programme and country | Design / Implementation Parameter | Variable | Effect Measure of change | Significance | Details/ explanation | |----|-------|-----------------------|-----------------------------------|----------|--------------------------|-------------|---------------------| | 1 | Baird et al. (2011) | ZCTP (Malawi) | Conditionality | Standardized math test score (TIMMS) | 0.006 Standard deviation | NS | UCT, after 2 years, 13-22 years Girls | | | | | | Standardized math test score (TIMMS) | 0.12 Standard deviation | 10% | CCT, after 2 years, 13-22 years, Girls | | 2 | Behrman et al. (2009) | PROGRESA / Oportunidades (Mexico) | Duration of Exposure | Math Test Score (Woodcock Johnson test) | -0.225 Percentage | NS | Extra 18 months of the programme when aged between 9-15, Female aged 9-15 in 1997 | | | | | | Math Test Score (Woodcock Johnson test) | -0.574 Percentage | NS | Extra 18 months of the programme when aged between 9-15, Male, aged 9-15 in 1997 |

Continued on next page Table A5.2.2 Summary of results for the role of cash transfer design and implementation parameters on education continued

| # | Study and country | Programme and Implementation Parameter | Variable | Effect Measure of change | Significance | Details/ explanation | |----|-------------------|-----------------------------------------|----------|--------------------------|--------------|---------------------| | 3 | Benhassine et al. (2013) | Main Recipient | Basic Arithmetic test – Summary Index (Based on ASER test, children 6-12) | -0.004 | Change in Score | NS | After 2 years, difference between LCT to mothers and LCT to fathers | | | Tayssir (Morocco) | Main Recipient | Basic Arithmetic test – Summary Index (Based on ASER test, children 6-12) | 0.567 | P value | NS | P-value for Mother different from Father | | | Tayssir (Morocco) | Conditionality | Basic Arithmetic test – Summary Index (Based on ASER test, children 6-12) | -0.056 | Change in Score | NS | After 2 years, difference between CCT to fathers and LCT to fathers | | | Tayssir (Morocco) | Conditionality | Basic Arithmetic test – Summary Index (Based on ASER test, children 6-12) | 0.034 | P value | 5% | P-value for CCT different from LCT |

Cognitive development

| 1 | Esteva (2012) | PROGRESA / Oportunidades (Mexico) | Duration of Exposure | Long term memory (log), assessed using the Woodcock-Munoz Test | 0.055 | Change in percentage | NS | Effect on children aged 2-6, approx. five years after the programme began. Effect of being a beneficiary for 18 months longer than in comparison group. | | | PROGRESA / Oportunidades (Mexico) | Duration of Exposure | Short term memory (log), assessed using the Woodcock-Munoz Test | 0.010 | Change in percentage | NS | As above | | | PROGRESA / Oportunidades (Mexico) | Duration of Exposure | Visual spatial integration, assessed using the Woodcock-Munoz Test | -0.014 | Change in percentage | NS | As above | | | PROGRESA / Oportunidades (Mexico) | Duration of Exposure | Language development (log), measured using the Peabody picture vocabulary test | 0.030 | Change in percentage | NS | Effect on children aged 3-6, approx. five years after the programme began. Effect of being a beneficiary for 18 months longer than in comparison group. | | | PROGRESA / Oportunidades (Mexico) | Duration of Exposure | Language development (log), measured using the Peabody picture vocabulary test | 0.101 | Change in percentage | NS | Effect on children aged 3-6, approx. five years after the programme began. Effect of additional exposure to the programme for the full time in-utero and partially during early childhood | | | PROGRESA / Oportunidades (Mexico) | Duration of Exposure | Language development (log), measured using the Peabody picture vocabulary test | -0.081 | Change in percentage | NS | Effect on children aged 3-6, approx. five years after the programme began. Effect of families receiving transfers for a longer period before having children. | | | PROGRESA / Oportunidades (Mexico) | Duration of Exposure | Visual spatial integration, assessed using the Woodcock-Munoz Test | 0.041 | Change in percentage | NS | Effect on children aged 2-6, approx. five years after the programme began. Effect of extra treatment in early childhood. | | | PROGRESA / Oportunidades (Mexico) | Duration of Exposure | Visual spatial integration, assessed using the Woodcock-Munoz Test | 0.012 | Change in percentage | NS | Effect on children aged 2-6, approx. five years after the programme began. Effect of additional exposure to the programme for the full time in-utero and partially during early childhood | | | PROGRESA / Oportunidades (Mexico) | Duration of Exposure | Visual spatial integration, assessed using the Woodcock-Munoz Test | -0.197 | Change in percentage | 5% | Effect on children aged 2-6, approx. five years after the programme began. Effect of families receiving transfers for a longer period before having children. | Table A5.2.2 Summary of results for the role of cash transfer design and implementation parameters on education continued

| # | Study | Programme and country | Design / Implementation Parameter | Variable | Effect Measure of change | Significance | Details/ explanation | |----|------------------------|-----------------------|-----------------------------------|---------------------------------------------------------------------------|--------------------------|-------------|-------------------------------------------------------------------------------------| | 1 | Esteva, 2012 | PROGRESA / Oportunidades (Mexico) | Duration of Exposure | Long term memory (log), assessed using the Woodcock-Munoz Test | 0.145 | 10% | Effect on children aged 2-6, approx. five years after the programme began. Effect of additional exposure to the programme for the full time in-utero and partially during early childhood | | | PROGRESA / Oportunidades (Mexico) | Duration of Exposure | Long term memory (log), assessed using the Woodcock-Munoz Test | -0.079 | NS | Effect on children aged 2-6, approx. five years after the programme began. Effect of families receiving transfers for a longer period before having children. | | | PROGRESA / Oportunidades (Mexico) | Duration of Exposure | Short term memory (log) assessed using the Woodcock-Munoz Test | 0.073 | NS | Effect on children aged 2-6, approx. five years after the programme began. Effect of additional exposure to the programme for the full time in-utero and partially during early childhood | | | PROGRESA / Oportunidades (Mexico) | Duration of Exposure | Short term memory (log) assessed using the Woodcock-Munoz Test | 0.027 | NS | Effect on children aged 2-6, approx. five years after the programme began. Effect of families receiving transfers for a longer period before having children. | | 2 | Fernald et al. (2008) | Oportunidades (Mexico) | Cumulative cash transfer (duration & transfer size) | Long-term memory | 0.12 | 1% | Effect of doubling cumulative cash transfers from median of 7500 to 15000 pesos on children 36-68 months old | | | Oportunidades (Mexico) | Cumulative cash transfer (duration & transfer size) | Short-term memory | 0.13 | 1% | Effect of doubling cumulative cash transfers from median of 7500 to 15000 pesos on children 36-68 months old | | | Oportunidades (Mexico) | Cumulative cash transfer (duration & transfer size) | Visual integration | 0.08 | 1% | Effect of doubling cumulative cash transfers from median of 7500 to 15000 pesos on children 36-68 months old | | 3 | Fernald et al. (2009) | Oportunidades (Mexico) | Cumulative cash transfers (duration & transfer size) | Verbal assessment score from Wechsler Abbreviated Scale of Intelligence — (WASI) | 0.73 | 1% | Effect of increase in cumulative cash transfer of 10000 pesos, after 10 years | | | Oportunidades (Mexico) | Duration of exposure | Verbal assessment score from WASI | 1.13 | Age-standardised z-score | NS | Early versus late treatment (an additional 18 months) on children aged 8-10, ten years later | | | Oportunidades (Mexico) | Cumulative cash transfers (duration & transfer size) | Cognitive assessment score from WASI | 0.47 | Age-standardised z-score | 1% | Effect of increase in cumulative cash transfer of 10000 pesos, after 10 years | | | Oportunidades (Mexico) | Duration of exposure | Cognitive assessment score from WASI | -1.19 | Age-standardised z-score | NS | Early versus late treatment (an additional 18 months) on children aged 8-10, ten years later | | 4 | Macours and Vakis (2012) | Atencion a Crisis (Nicaragua) | Complementary Activities | Cognitive and socio-emotional outcomes index (comprised of five different indicators) | 0.016 | Change in standard deviation | NS | Lump sum payment treatment compared to basic treatment, effect after 9 months’ exposure. Averaged across 3 different CCT treatment arms | | | Atencion a Crisis (Nicaragua) | Complementary Activities | Cognitive and socio-emotional outcomes index (comprised of six different indicators) | -0.008 | Change in standard deviation | NS | Lump sum payment treatment compared to basic treatment, effect 2 years after programme finished. Averaged across three different CCT treatment arms |

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### Table A5.2.2 Summary of results for the role of cash transfer design and implementation parameters on education continued

| # | Study | Programme and country | Design / Implementation Parameter | Variable | Effect Measure of change | Significance | Details/ explanation | |----|-------|-----------------------|-----------------------------------|----------|--------------------------|-------------|---------------------| | 5 | Manley et al. (2015) | PROGRESA / Oportunidades (Mexico) | Duration of exposure | Verbal WASI (Wechsler Abbreviated Scale of Intelligence) score | 1.25 Change in score | NS | CCT, effect of 18 additional months in PROGRESA | | | | PROGRESA / Oportunidades (Mexico) | Transfer Amount | Verbal WASI (Wechsler Abbreviated Scale of Intelligence) score | 0.7 Change in score | 1% | CCT, effect of larger potential transfer amount | | | | PROGRESA / Oportunidades (Mexico) | Duration of exposure | Cognitive WASI (Wechsler Abbreviated Scale of Intelligence) score | -1.2 Change in score | NS | CCT, effect of 18 additional months in PROGRESA | | | | PROGRESA / Oportunidades (Mexico) | Transfer Amount | Cognitive WASI (Wechsler Abbreviated Scale of Intelligence) score | 0.46 Change in score | 10% | CCT, effect of larger potential transfer amount | | | | PROGRESA / Oportunidades (Mexico) | Duration of exposure | Strengths and difficulties questionnaire | -0.14 Change in score | 5% | CCT, effect of 18 additional months in PROGRESA | | | | PROGRESA / Oportunidades (Mexico) | Transfer Amount | Strengths and difficulties questionnaire | -0.02 Change in score | NS | CCT, effect of larger potential transfer amount |

9 Test 22 of the Woodcock Johnson tests: Letter-word Identification consisting of showing those taking the test various pictures, letters and progressively harder words where the examinee is asked to say what is in the picture, and then to state letters, and then words. In the case of words, the examinee must pronounce the word correctly for it to be classified as a correct answer.

10 Test 26 of the Woodcock Johnson test: Dictation where the examiner reads aloud letters and words and the examinee must write down the letter/word correctly.

11 TIMMS stands for Trends in Mathematics and Science Study, which is a cycle of internationally comparative assessments in mathematics and science carried out at the fourth and eighth grades every 4 years. Authors also borrowed five mathematics questions from the 2007 TIMMS and incorporated them into an independently developed mathematics test (Non-TIMMS).

## Summary tables for results for Health and Nutrition

### Table A5.3.1 Summary of results for cash transfer effects disaggregated by gender for health and nutrition indicators

| # | Study | Programme | Outcome indicator and treatment population | Effect | Measure of change | Significance | Details | |---|-------|-----------|---------------------------------------------|--------|-------------------|--------------|---------| | **Health service use** | | | | | | | | | 1 | Akresh et al. (2012) | NCT (Burkina Faso) | Number of child preventative health care visits | 0.48 | Visits | 5% | Household receiving CCT (girls under 60 months) | | | Akresh et al. (2012) | NCT (Burkina Faso) | Number of child preventative health care visits | 0.39 | Visits | NS | Household receiving CCT (boys under 60 months) | | | Akresh et al. (2012) | NCT (Burkina Faso) | Number of child preventative health care visits | -0.106 | Visits | NS | Household receiving UCT (girls under 60 months) | | | Akresh et al. (2012) | NCT (Burkina Faso) | Number of child preventative health care visits | -0.045 | Visits | NS | Household receiving UCT (boys under 60 months) | | 2 | Evans et al. (2014) | TSAF (Tanzania) | Number of health visits (children up to 2 years old) | -3.8 | Visits | 5% | Girls (after 31 to 34 months) | | | Evans et al. (2014) | TSAF (Tanzania) | Number of health visits (children up to 2 years old) | -2.3 | Visits | NS | Boys (after 31 to 34 months) | | | Evans et al. (2014) | TSAF (Tanzania) | Number of health visits (aged 60 plus) | -0.58 | Visits | 10% | Women aged 60 plus | | | Evans et al. (2014) | TSAF (Tanzania) | Number of health visits (aged 60 plus) | -0.15 | Visits | NS | Men aged 60 plus | | 3 | Levy and Ohls (2007) | PATH (Jamaica) | Visits to health facilities in the past six months (children under 6) | 0.45 | Visits | NS | Girls in beneficiary households | | | Levy and Ohls (2007) | PATH (Jamaica) | Visits to health facilities in the past six months (children under 6) | 0.16 | Visits | NS | Boys in beneficiary households | | **Health service use (gender of household head)** | | | | | | | | | 1 | World Bank (2011) | PKH (Indonesia) | Number of prenatal visits | 2.3 | Visits | 1% | Female-headed households | | | World Bank (2011) | PKH (Indonesia) | Number of prenatal visits | 0.5 | Visits | 5% | Male-headed households | | | World Bank (2011) | PKH (Indonesia) | Number of post-natal visits | -0.14 | Visits | NS | Female-headed households | | | World Bank (2011) | PKH (Indonesia) | Number of post-natal visits | 0.38 | Visits | 5% | Male-headed households | | **Child anthropometric measures (gender of household head)** | | | | | | | | | 1 | World Bank (2011) | PKH (Indonesia) | Height-for-age (0-36 months old) | -0.049 | NS | Female-headed households | | | World Bank (2011) | PKH (Indonesia) | Height-for-age (0-36 months old) | 0.104 | NS | Male-headed households | | | World Bank (2011) | PKH (Indonesia) | Weight-for-age (0-36 months old) | 0.363 | NS | Female-headed households | | | World Bank (2011) | PKH (Indonesia) | Weight-for-age (0-36 months old) | -0.094 | NS | Male-headed households | | | World Bank (2011) | PKH (Indonesia) | Weight-for-height z-score (children up to 36 months) | 0.71 | NS | Female-headed households | | | World Bank (2011) | PKH (Indonesia) | Weight-for-height z-score (children up to 36 months) | -0.26 | 10% | Male-headed households | | **Child anthropometric measures (individual level)** | | | | | | | | | 1 | Cheema et al. (2014) | BISP (Pakistan) | Proportion of children stunted (aged up to 59 months) | 0.1721 | Percentage points | NS | Boys | | | Cheema et al. (2014) | BISP (Pakistan) | Proportion of children stunted (aged up to 59 months) | -0.3745 | Percentage points | 5% | Girls | | | Cheema et al. (2014) | BISP (Pakistan) | Proportion of children wasted (aged up to 59 months) | -0.2226 | Percentage points | NS | Boys | | | Cheema et al. (2014) | BISP (Pakistan) | Proportion of children wasted (aged up to 59 months) | 0.1702 | Percentage points | NS | Girls |

### Table A5.3.2 Summary of results for the role of cash transfer design and implementation parameters on health and nutrition

| # | Study | Programme and country | Outcome indicator and treatment population | Effect | Measure of change | Significance | Details/ explanation | |----|-------|-----------------------|---------------------------------------------|--------|-------------------|--------------|---------------------| | **Main recipient** | | | | | | | | | 1 | Akresh et al. (2012) | NCT (Burkina Faso) | Number of preventative health visits for child over past year | 0.45 | Visits | 5% | CCTs targeted to mothers | | | | NCT (Burkina Faso) | Number of preventative health visits for child over past year | 0.42 | Visits | NS | CCTs targeted to fathers | | | | NCT (Burkina Faso) | Number of preventative health visits for child over past year | 0.05 | Visits | NS | UCTs targeted to mothers | | | | NCT (Burkina Faso) | Number of preventative health visits for child over past year | -0.22 | Visits | NS | UCTs targeted to fathers | | 2 | Behrman and Parker (2013) | PROGRESA/Oportunidades (Mexico) | Probability of attending clinic in past year | 0.114 | Percentage point | 10% | Transfer being received by the elderly person | | | | PROGRESA/Oportunidades (Mexico) | Probability of attending clinic in past year | 0.255 | Percentage point | 1% | Transfer being received by a younger woman in the house | | **Transfer size** | | | | | | | | | 1 | Davis et al. (2002) | PROGRESA (Mexico) | Whether child had a health check-up (0 to 5 years old) | 0.0078 | Percentage point | 1% | Additional peso of transfer (includes non-beneficiaries) | | | | PROCAMPO (Mexico) | Whether child had a health check-up (0 to 5 years old) | 0.0026 | Percentage point | NS | Additional peso of transfer (includes non-beneficiaries) | | 2 | Esteva (2012) | PROGRESA (Mexico) | Being stunted (children 2-6 years in 2003) | -0.0199 | Percentage point | NS | Effect of increase in amount of cash component (equal to $344 Pesos during first year of life) | | | | PROGRESA (Mexico) | Height-for-age z-score | 0.1539 | Z-score | NS | Effect of increase in amount of cash component (equal to $344 Pesos during first year of life) | | | | PROGRESA (Mexico) | Weight-for-age z-score | 0.1484 | Z-score | NS | Effect of increase in amount of cash component (equal to $344 Pesos during first year of life) | | 3 | Manley (2015) | Oportunidades (Mexico) | Height-for-age | 0.07 | Z-score | 1% | Effect of additional Peso of transfer | | 4 | Merttens et al. (2013) | HSNP (Kenya) | Mean dietary diversity score | Not reported | Score | NS | (Does not report coefficient of the non-significant result) | | **Duration of exposure** | | | | | | | | | 1 | Behrman and Parker (2013) | PROGRESA/Oportunidades (Mexico) | Probability of attending a clinic | 0.048 | Percentage point | 5% | Being in the programme for an extra 1.5 years (women) | | | | PROGRESA/Oportunidades (Mexico) | Probability of attending a clinic | 0.027 | Percentage point | NS | Being in the programme for an extra 1.5 years (men) | | | | PROGRESA/Oportunidades (Mexico) | Probability of attending a clinic | 0.20 | Percentage point | 1% | Being in the programme for an extra 4 years (women) | | | | PROGRESA/Oportunidades (Mexico) | Probability of attending a clinic | 0.17 | Percentage point | 1% | Being in the programme for an extra 4 years (men) | | | | PROGRESA/Oportunidades (Mexico) | Probability of attending a clinic | 0.23 | Percentage point | 1% | Being in the programme for an extra 5.5 years (women) | | | | PROGRESA/Oportunidades (Mexico) | Probability of attending a clinic | 0.20 | Percentage point | 1% | Being in the programme for an extra 5.5 years (men) | | | | PROGRESA/Oportunidades (Mexico) | Probability of attending a clinic | 0.26 | Percentage point | 1% | Being in the programme for an extra 5.5 years (women aged 70 +) | | | | PROGRESA/Oportunidades (Mexico) | Probability of attending a clinic | 0.08 | Percentage point | NS | Being in the programme for an extra 5.5 years (men aged 70 +) |

*Continued on next page*

### Table A5.3.2 Summary of results for the role of cash transfer design and implementation parameters on health and nutrition continued

| # | Study | Programme and country | Outcome indicator and treatment population | Effect Measure of change | Significance | Details/ explanation | |----|--------------------------------------------|-----------------------|---------------------------------------------|--------------------------|--------------|--------------------------------------------------------------------------------------| | 1 | Behrman and Parker (2013) | PROGRESA / Oportunidades (Mexico) | Probability of attending a clinic | 0.09 Percentage point | 10% | Being in the programme for an extra 5.5 years (women aged 60-69) | | | | | Probability of attending a clinic | 0.24 Percentage point | 1% | Being in the programme for an extra 5.5 years (men aged 60-69) | | | | | Probability of attending a clinic | 0.29 Percentage point | 1% | Being in the programme for an extra 5.5 years (women aged 50-59) | | | | | Probability of attending a clinic | 0.21 Percentage point | 1% | Being in the programme for an extra 5.5 years (men aged 50-59) | | | | | Probability of attending a clinic | 0.26 Percentage point | 1% | Transfer being received by the elderly woman | | | | | Probability of attending a clinic | 0.11 Percentage point | 10% | Transfer being received by a younger woman in the house | | 2 | Buser et al. (2014) | BDH (Ecuador) | Weight-for-age | 0.596 Z-score | 1% | Continuing to receive transfer, compared to losing it two years ago | | | | | Height-for-age | 0.367 Z-score | 10% | Continuing to receive transfer, compared to losing it two years ago | | | | | Weight-for-height | 0.495 Z-score | 1% | Continuing to receive transfer, compared to losing it two years ago | | | | | Underweight | -0.027 Percentage point | NS | Continuing to receive transfer, compared to losing it two years ago | | | | | Stunted | -0.136 Percentage point | 5% | Continuing to receive transfer, compared to losing it two years ago | | | | | Weight-for-age | 1.397 Percentage point | 1% | Continuing to receive transfer, compared to losing it two years ago | | | | | Height-for-age | 0.985 Percentage point | 1% | Continuing to receive transfer, compared to losing it two years ago | | | | | Weight-for-height | 0.915 Percentage point | 1% | Continuing to receive transfer, compared to losing it two years ago | | | | | Received child health check | 0.131 Percentage point | NS | Continuing to receive transfer, compared to losing it two years ago | | 3 | Esteva (2012) | Oportunidades (Mexico) | Being stunted (children 2-6 years in 2003) | 0.0226 Percentage point | NS | Being in early treatment group (associated average of $484, $530 and $1959 Mexican Pesos more during pregnancy, first year and cumulatively than ‘late entry’ households) | | | | | Height-for-age z-score | -0.0279 Z-score | NS | (As above) | | | | | Weight-for-age z-score | -0.0077 Z-score | NS | (As above) | | 4 | Fernald et al. (2008) | Oportunidades (Mexico) | Height-for-age (24 to 68 month children) | 0.2 Z-score | 1% | Effect of doubling cash transfers from the median of 7500 to 15000 pesos ($806 to $1612) | | | | | Whether stunted or not (24 to 68 month children) | -0.1 Percentage point | 1% | Effect of doubling cash transfers from the median of 7500 to 15000 pesos ($806 to $1612) | | 5 | Fernald et al. (2009) | Oportunidades (Mexico) | Height-for-age | 0.03 Z-score | 1% | Effect size of increase in cash transfer of around $926 (cumulative cash transfers received) | | 6 | Manley et al. (2015) | Oportunidades (Mexico) | Height-for-age | 0.03 Z-score | NS | Effect of 18 additional months on the programme | | 7 | Perova and Vakis, (2012) | Juntos (Peru) | Received health checks in last 3 months (for children under 5) | 0.13 Percentage point | 5% | Being a beneficiary household for over 36 months |

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### Table A5.3.2 Summary of results for the role of cash transfer design and implementation parameters on health and nutrition continued

| # | Study and country | Programme and treatment population | Outcome indicator and treatment population | Effect Measure of change | Significance | Details/ explanation | |----|-------------------|-------------------------------------|---------------------------------------------|--------------------------|-------------|----------------------| | **Conditionalities** | | | | | | | | 1 | Attanasio et al. (2015) | Familias en Acción (Colombia) | Number of preventative health care visits (Children under 36 months) | -0.574 | Visits | 1% Effect of there not being a condition of health visits (versus presence of condition) | | 2 | Akresh et al. (2012) | NCTPP (Burkina Faso) | Number of routine preventative health clinic visits for child under 60 months | 0.431 | Visits | 5% Conditional on obtaining quarterly child growth monitoring at health clinics for all children under 60 months old | | | | NCTPP (Burkina Faso) | Number of routine preventative health clinic visits for child under 60 months | -0.079 | Visits | NS Receiving unconditional transfers | | 3 | Benedetti et al. (2015) | Bono 10,000 (Honduras) | Number of prenatal check-ups during last or current pregnancy | 0.269 | Visits | NS Households where transfers conditioned on regular attendance at health centres | | | | Bono 10,000 (Honduras) | Number of prenatal check-ups during last or current pregnancy | 0.431 | Visits | NS Households where transfers not conditional on regular health centre visits nor labelled as health transfers | | | | Bono 10,000 (Honduras) | Women received postnatal check-up in 10 days after birth | 0.212 | Percentage change | 5% Households where transfers conditioned on regular attendance at health centres | | | | Bono 10,000 (Honduras) | Women received postnatal check-up in 10 days after birth | 0.118 | Percentage change | NS Households where transfers not conditional on regular health centre visits nor labelled as health transfers | | **Payment mechanisms** | | | | | | | | 1 | Aker et al. (2011) | Mobile money experiment (Niger) | Household diet diversity score (number of food groups eaten in past 24 hours, out of 12) | 0.5 | Number of food groups | 5% Whether household received cash via e-payment using a mobile phone | | 2 | Aker et al. (2014) | Mobile money experiment (Niger) | Household diet diversity score (number of food groups eaten in past 24 hours, out of 12) | 0.07 | Difference in means | 1% Whether household received cash via e-payment using a mobile phone | | | | Mobile money experiment (Niger) | Weight-for-height z-score | 0 | Z-score | NS Whether household received cash via e-payment using a mobile phone | | | | Mobile money experiment (Niger) | Prevalence of wasting | 0.43 | Percentage point | NS Whether household received cash via e-payment using a mobile phone | | **Complementary interventions and supply side services** | | | | | | | | 1 | Langendorf et al. (2014) | Prospective nutrition study (Niger) | Moderate acute malnutrition of children 6-23 months | 2.3 | Hazard ratio | 1% Effect of also receiving supplementary foods (HQ-LNS 500 kcal/day (Supplementary Plumpy, Nutriset)) for children 6-23 months | | | | Prospective nutrition study (Niger) | Moderate acute malnutrition of children 6-23 months | 2.42 | Hazard ratio | 1% Effect of also receiving supplementary foods (MQ-LNS 250 kcal/day (Plumpy/Doz, Nutriset)) for children 6-23 months | | | | Prospective nutrition study (Niger) | Moderate acute malnutrition of children 6-23 months | 2.07 | Hazard ratio | 1% Effect of also receiving supplementary foods (Super Cereal Plus 820 kcal/day (Michiels and Cerfar)) |

## Summary tables for results for Savings, Investment and Production

### Table A5.4.1 Summary of results for cash transfer effects disaggregated by gender for savings, investment and production

| # | Study | Programme | Indicator | Effect | Measure of change | Significance | Details | |----|------------------------|-----------|---------------------------------------------------------------------------|--------|-------------------|--------------|------------------------------| | 1 | Asfaw et al. (2014) | CT-OVC (Kenya) | Proportion of female-headed households owning small livestock (sheep, goat, and so forth) | 0.06 | Percentage point change | 10% | Female headed household | | | | CT-OVC (Kenya) | Female-headed household participation in non-farm enterprise | 0.072 | Percentage point change | 5% | Female headed household | | 2 | Blattman et al. (2012) | YDP (Uganda) | Tools and machines acquired since baseline (beneficiary males) | 791.90 | '000s UGX | 1% | Male beneficiaries | | | | YDP (Uganda) | Tools and machines acquired since baseline (beneficiary females) | -409.80| '000s UGX | 5% | Difference in effect compared to male beneficiaries | | | | YDP (Uganda) | Stock of raw materials, tools, and machines (beneficiary males) | 658.55 | '000s UGX | 1% | Male beneficiaries | | | | YDP (Uganda) | Stock of raw materials, tools, and machines (beneficiary females) | -408.07| '000s UGX | 5% | Difference in effect compared to male beneficiaries | | 3 | Blattman et al. (2015) | WINGS (Uganda) | Impacts of the full program (Phase 1) on whether female recipient started enterprise since baseline 16 months after grants | 0.473 | Percentage point change | 1% | Female recipient | | | | WINGS (Uganda) | Impacts of the full program (Phase 1) on whether male recipient started enterprise since baseline 16 months after grants | 0.595 | Percentage point change | 1% | Male recipient | | | | WINGS (Uganda) | Impacts of the full program (Phase 1) on amount of savings by female recipient 16 months after grants | 101.009| Level change | 1% | Female recipient | | | | WINGS (Uganda) | Impacts of the full program (Phase 1) on amount of savings by male recipient 16 months after grants | 169.695| Level change | 1% | Male recipient | | | | WINGS (Uganda) | Impacts of the full program (Phase 1) on amount of debt by female recipient 16 months after grants | 2.631 | Level change | 5% | Female recipient | | | | WINGS (Uganda) | Impacts of the full program (Phase 1) on amount of debt by male recipient 16 months after grants | 4.981 | Level change | 10% | Male recipient | | 4 | Covarrubias et al. (2012) | SCTP (Malawi) | Female-headed household ownership of hoes | 0.23 | Percentage point change | 1% | Female headed household | | | | SCTP (Malawi) | Female-headed household ownership of axes | 0.436 | Percentage point change | 1% | Female headed household | | | | SCTP (Malawi) | Female-headed household ownership of goats | 0.52 | Percentage point change | 1% | Female headed household | | | | SCTP (Malawi) | Female-headed household ownership of chickens | 0.612 | Percentage point change | 1% | Female headed household | | 5 | Evans et al. (2014) | Community-based CCT (Tanzania) | Ownership at endline of indigenous goats (including kids) – female headed hhs | 0.23 | Percentage point change | NS | Female headed household | | | | Community-based CCT (Tanzania) | Ownership at endline of indigenous goats (including kids) – male headed hhs | 0.47 | Percentage point change | 5% | Male headed household | | | | Community-based CCT (Tanzania) | Ownership at local chickens (excluding chicks) – female headed hhs | 1.62 | Percentage point change | 1% | Female headed household | | | | Community-based CCT (Tanzania) | Ownership at endline Indigenous goats (including kids) – male headed hhs | 0.82 | Percentage point change | NS | Male headed household |

Continued on next page

### Table A5.4.1 Summary of results for cash transfer effects disaggregated by gender for savings, investment and production continued

| # | Study | Programme | Indicator | Effect | Measure of change | Significance | Details | |----|--------------------------------|-----------|------------------------------------------------|--------|-------------------|--------------|------------------------------| | 6 | Handa et al. (2014) | LEAP (Ghana) | Any savings (female headed hhs) | 0.07 | Percentage point change | 10% | Female headed household | | | | LEAP (Ghana) | Any savings (male headed hhs) | 0.147 | Percentage point change | 10% | Male headed household | | | | LEAP (Ghana) | Used Fertiliser (female headed hhs) | -0.015 | Percentage point change | NS | Female headed household | | | | LEAP (Ghana) | Used Fertiliser (male headed hhs) | -0.074 | Percentage point change | NS | Male headed household | | | | LEAP (Ghana) | Seeds Expenses (female headed hhs) | 21.58 | Level change | 5% | Female headed household | | | | LEAP (Ghana) | Seeds Expenses (male headed hhs) | 33.81 | Level change | 5% | Male headed household | | | | LEAP (Ghana) | Hold loan (female headed hhs) | -0.065 | Percentage point change | NS | Female headed household | | | | LEAP (Ghana) | Hold loan (male headed hhs) | -0.004 | Percentage point change | NS | Male headed household | | | | LEAP (Ghana) | Amount outstanding (female headed hhs) | -0.28 | Level change | NS | Female headed household | | | | LEAP (Ghana) | Amount outstanding (male headed hhs) | -1.003 | Level change | NS | Male headed household | | 7 | Haushofer and Shapiro (2013) | Give Directly (Kenya) | Value of livestock (female recipients) | 7.86 | Level change | NS | Female recipients | | | | Give Directly (Kenya) | Value of agricultural tools (USD) – female recipients | -2.22 | Level change | NS | Female recipients | | | | Give Directly (Kenya) | Value of savings (USD) – female recipients | -3.43 | Level change | NS | Female recipients | | 8 | Martinez (2004) | Bonosol (Bolivia) | Probability of investing on fertiliser, female oldest HH member | 0.088 | Percentage point change | 10% | Female oldest household member | | | | Bonosol (Bolivia) | Probability of investing on seeds, female oldest HH member | 0.062 | Percentage point change | NS | Female oldest household member | | | | Bonosol (Bolivia) | Monthly expenditures on seeds, female oldest HH member | 5.108 | Level change | 5% | Female oldest household member |

### Table A5.4.2 Summary of results for the role of cash transfer design and implementation parameters on savings, investment and production

| # | Study | Programme | Variable and treatment population | Effect | Measure of change | Significance | Details | |----|------------------------------|-----------|---------------------------------------------------------------------------------------------------|--------|-------------------|--------------|----------------------------------------------| | | Main recipient | | | | | | | | 1 | Haushofer and Shapiro (2013) | Give Directly (Kenya) | Value of livestock – female recipient vs male | 7.86 | Level change | NS | Main recipient (female vs male) | | | | | Value of savings – female recipient vs male | -3.43 | Level change | NS | Main recipient (female vs male) | | | | | Non-ag business investment in durables, monthly (USD) – female recipient vs male | -0.15 | Level change | NS | Main recipient (female vs male) | | | Transfer size and frequency | | | | | | | | 1 | Haushofer and Shapiro (2013) | Give Directly (Kenya) | Value of livestock – monthly transfer vs lump-sum | 2.07 | Level change | NS | Transfer frequency | | | | | Value of cows – monthly transfer vs lump-sum | -13.46 | Level change | NS | Transfer frequency | | | | | Value of small livestock – monthly transfer vs lump-sum | 6.84 | Level change | NS | Transfer frequency | | | | | Value of livestock – large vs small transfer | 63.19 | Level change | 5% | Transfer size | | | | | Value of cows – large vs small transfer | 43.79 | Level change | 10% | Transfer size | | | | | Value of small livestock – large vs small transfer | 20.09 | Level change | 1% | Transfer size | | | | | Value of savings – monthly transfer vs lump-sum | 1.81 | Level change | NS | Transfer frequency | | | | | Value of savings – large vs small transfer | 10.22 | Level change | 5% | Transfer size | | | | | Non-ag business investment in durables, monthly (USD) – monthly transfer vs lump-sum | 0.01 | Level change | NS | Transfer frequency | | | | | Non-ag business investment in durables, monthly (USD) – large vs small transfer | -0.15 | Level change | NS | Transfer size | | | Duration of exposure | | | | | | | | 1 | Gertler et al. (2012) | Oportunidades (Mexico) | Draft animal ownership – long term 2003 sample | 0.031 | Percentage point | NS | Longer exposure to programme – four years after control households were incorporated | | | | | Productive animal ownership – long term 2003 sample | 0.02 | Percentage point | NS | Longer exposure to programme – four years after control households were incorporated | | | | | Productive loans | 0.004 | Percentage point | 5% | Longer exposure to programme – four years after control households were incorporated | | 2 | Maluccio (2010) | RPS (Nicaragua) | Number of productive agricultural goods (2002) – ploughs, water pumps, sprayers, tools, and carts | 0.086 | Level change | 10% | Shorter exposure | | | | | Value of productive agricultural goods (2002) – ploughs, water pumps, sprayers, tools, and carts | 3.4 | Level change | NS | Shorter exposure | | | | | Number of productive agricultural goods (2004) – ploughs, water pumps, sprayers, tools, and carts | -0.023 | Level change | NS | Longer exposure | | | | | Value of productive agricultural goods (2004) – ploughs, water pumps, sprayers, tools, and carts | -18.2 | Level change | NS | Longer exposure | | | | | Number of types of animals owned (cattle, work animals and poultry) (2002) | -0.032 | Level change | NS | Shorter exposure | | | | | Value of all animals owned (cattle, work animals and poultry) (2002) | -110.1 | Level change | NS | Shorter exposure |

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### Table A5.4.2 Summary of results for the role of cash transfer design and implementation parameters on savings, investment and production continued

| # | Study | Programme | Variable and treatment population | Effect | Measure of change | Significance | Details | |----|------------------------|-----------|---------------------------------------------------------------------------------------------------|--------|-------------------|--------------|------------------------------| | 2 | Maluccio (2010) | RPS | Number of types of animals owned (cattle, work animals and poultry) (2004) | -0.008 | Level change | NS | Longer exposure | | | RPS (Nicaragua) | | Value of all animals owned (cattle, work animals and poultry) (2004) | 208.4 | Level change | NS | Longer exposure |

#### Targeting mechanism

| # | Study | Programme | Variable and treatment population | Effect | Measure of change | Significance | Details | |----|------------------------|-----------|---------------------------------------------------------------------------------------------------|--------|-------------------|--------------|------------------------------| | 1 | Mertens et al. (2015) | SAGE | Proportion of HHs owning livestock (Senior Citizens Grant) | 4.1 | Percentage point | NS | SCG (elderly) vs VFSG | | | | | Proportion of HHs owning livestock (Vulnerable Family Support Grant) | 9.3 | Percentage point | 1% | SCG (elderly) vs VFSG | | | | | Proportion of households purchasing livestock in last 12 months (Senior Citizens Grant) | 9.3 | Percentage point | 5% | SCG (elderly) vs VFSG | | | | | Proportion of households purchasing livestock in last 12 months (Vulnerable Family Support Grant) | 26.2 | Percentage point | 1% | SCG (elderly) vs VFSG | | | | | Proportion of households owning cattle (Senior Citizens Grant) | -0.28 | Percentage point | NS | SCG (elderly) vs VFSG | | | | | Proportion of households owning cattle (Vulnerable Family Support Grant) | 6.7 | Percentage point | 1% | SCG (elderly) vs VFSG | | | | | Proportion of households owning goats (Senior Citizens Grant) | 2.1 | Percentage point | NS | SCG (elderly) vs VFSG | | | | | Proportion of households owning goats (Vulnerable Family Support Grant) | 7.3 | Percentage point | 5% | SCG (elderly) vs VFSG | | | | | Proportion of households purchasing productive assets in last 12 months (Senior Citizens Grant) | 0.24 | Percentage point | NS | SCG (elderly) vs VFSG | | | | | Proportion of households purchasing productive assets in last 12 months (Vulnerable Family Support Grant) | 8.8 | Percentage point | 5% | SCG (elderly) vs VFSG | | | | | Mean total value of productive assets purchased (SCG) (2012 prices, UGX) | 500 | Percentage point | NS | SCG (elderly) vs VFSG | | | | | Mean total value of productive assets purchased (VFSG) (2012 prices, UGX) | 500 | Percentage point | NS | SCG (elderly) vs VFSG | | | | | Proportion of households reporting current cash savings (Senior Citizens Grant) | 4.9 | Percentage point | NS | SCG (elderly) vs VFSG | | | | | Proportion of households reporting current cash savings (VFSG) | 9.5 | Percentage point | 5% | SCG (elderly) vs VFSG | | | | | Mean total value of current savings, for those with any savings (2012 prices, UGX) – (Senior Citizens Grant) | -156,000 | Level change | NS | SCG (elderly) vs VFSG | | | | | Mean total value of current savings, for those with any savings (2012 prices, UGX) – (VFSG) | 90,500 | Level change | NS | SCG (elderly) vs VFSG | | | | | Proportion of households reporting borrowing money in last 12 months (SCG) | 7.3 | Percentage point | 10% | SCG (elderly) vs VFSG | | | | | Proportion of households reporting borrowing money in last 12 months (VFSG) | -1.3 | Percentage point | NS | SCG (elderly) vs VFSG |

Continued on next page

### Table A5.4.2 Summary of results for the role of cash transfer design and implementation parameters on savings, investment and production continued

| # | Study | Programme | Variable and treatment population | Effect | Measure of change | Significance | Details | |----|--------------------------------|--------------------|---------------------------------------------------------------------------------------------------|--------|-------------------|--------------|----------------------------------------------| | 1 | Merttens et al. (2015) | SAGE (Uganda) | Mean total value of current outstanding debt, for those with outstanding debt (2012 prices, UGX) (SCG) | 7500 | Level change | NS | SCG (elderly) vs VFSG | | | | SAGE (Uganda) | Mean total value of current outstanding debt, for those with outstanding debt (2012 prices, UGX) (VFSG) | 31000 | Level change | NS | SCG (elderly) vs VFSG | | | | SAGE (Uganda) | Proportion of households reporting being able to borrow a large (e.g. UGX 60,000 or more) amount of cash in an emergency (SCG) | 11 | Percentage point | 1% | SCG (elderly) vs VFSG | | | | SAGE (Uganda) | Proportion of households reporting being able to borrow a large (e.g. UGX 60,000 or more) amount of cash in an emergency (VFSG) | 10 | Percentage point | 5% | SCG (elderly) vs VFSG |

#### Payment mechanism

| # | Study | Programme | Variable and treatment population | Effect | Measure of change | Significance | Details | |----|--------------------------------|--------------------|---------------------------------------------------------------------------------------------------|--------|-------------------|--------------|----------------------------------------------| | 1 | Aker et al. (2011) | Concern Worldwide CT (Niger) | Types of crops grown (Zap m-transfer) | 0.49 | Number of different types of crops | 5% | DD estimator between Zap and cash households | | | | Concern Worldwide CT (Niger) | Types of crops grown (Placebo transfer) | 0.12 | Number of different types of crops | NS | DD estimator between placebo and cash households | | | | Concern Worldwide CT (Niger) | Number of asset categories owned (out of 12) (Zap m-transfer) | 0.66 | Number asset categories | 1% | DD estimator between Zap and cash households | | | | Concern Worldwide CT (Niger) | Number of asset categories owned (out of 12) (Placebo transfer) | 0.2 | Number asset categories | NS | DD estimator between placebo and cash households |

#### Complementary interventions and supply side services

| # | Study | Programme | Variable and treatment population | Effect | Measure of change | Significance | Details | |----|--------------------------------|--------------------|---------------------------------------------------------------------------------------------------|--------|-------------------|--------------|----------------------------------------------| | 1 | Blattman et al. (2015) | WINGS (Uganda) | Impacts of the full program (Phase 2) on amount of savings by recipients 12-month after grant as effect of 1-2 follow-ups (supervision without advice) | 26.41 | Level change | 10% | Supervision without advice received | | | Blattman et al. (2015) | WINGS (Uganda) | Impacts of the full program (Phase 2) on whether recipients started enterprise 12 months after grant as effect of additional 1-2 follow-ups (supervision) | 0.107 | Percentage point | 1% | Supervision without advice received | | 2 | Green et al. (2015) | WINGS (Uganda) | Currently doing business (women selected and trained with partner compared to women without) | -0.09 | Percentage point | 10% | Women selected and trained with partner compared to women without | | | WINGS (Uganda) | Started enterprise since baseline (women selected and trained with partner compared to women without) | 0.02 | Percentage point | NS | Women selected and trained with partner compared to women without | | 3 | Macours and Vakis (2009) | Atencion a Crisis (Nicaragua) | Value of business assets (CT + training) | -17.8 | Level change | NS | Vocational training | | | Atencion a Crisis (Nicaragua) | Value of business assets (CT + productive grant) | 235.3 | Level change | 10% | Productive grant | | | Atencion a Crisis (Nicaragua) | Value of livestock sold or self-consumed (CT + training) | -33.57 | Level change | NS | Vocational training | | | Atencion a Crisis (Nicaragua) | Value of livestock sold or self-consumed (CT + productive grant) | 221.8 | Level change | 10% | Productive grant | | 4 | Karlan et al. (2014) | IPA RCT (Ghana) | Value of chemicals used | 55.63 | US dollars | 1% | Capital grant | | | IPA RCT (Ghana) | Value of chemicals used relative to receiving insurance alone (figure in brackets is total effect for grant + insurance) | 66.44 | US dollars | 1% (difference compared to insurance alone) | Capital grant + weather insurance |

Continued on next page

### Table A5.4.2 Summary of results for the role of cash transfer design and implementation parameters on savings, investment and production continued

| # | Study | Programme | Variable and treatment population | Effect | Measure of change | Significance | Details | |----|------------------------|-----------|---------------------------------------------------------------------------------------------------|--------|-------------------|--------------|----------------------------------------------| | 4 | Karlan et al. (2014) | IPA RCT (Ghana) | Household has nonfarm income generating activity (binary) | -0.04 | Percentage point | NS | Capital grant | | | IPA RCT (Ghana) | | Whether household has nonfarm income generating activity relative to receiving insurance alone | 0.07 | Percentage point | 5% (difference compared to insurance alone) | Capital grant + weather insurance | | | IPA RCT (Ghana) | | Post-harvest assets (livestock and grain) | 606.12 | US dollars | 5% | Capital grant | | | IPA RCT (Ghana) | | Post-harvest assets (livestock and grain) relative to receiving insurance alone | 310.66 | US dollars | NS (difference compared to insurance alone) | Capital grant + weather insurance |

12 Placebo transfer is a normal cash disbursement plus one-off donation of mobile phone

13 Note these are not all productive assets

### Summary tables for results for Employment

#### Table A5.5.1 Summary of results for overall cash transfer effect on adult labour participation – by gender

| # | Study | Programme and country | Outcome variable | Treatment population | Effect | Measure of change | Significance | |----|--------------------------------------------|-----------------------|------------------|----------------------|--------|-------------------|--------------| | 1 | Alzua et al. (2013) | PRAF (Honduras) | Whether working | Female | -0.010 | Percentage point | NS | | | | | | Male | -0.005 | Percentage point | NS | | | | RPS (Nicaragua) | Whether working | Female | -0.020 | Percentage point | NS | | | | | | Male | -0.009 | Percentage point | NS | | | | PROGRESA (Mexico) | Whether working | Female | -0.02 | Percentage point | NS | | | | | | Male | 0.003 | Percentage point | NS | | 2 | Ardington et al. | SA-OAP (South Africa) | Whether working | Females 17-51 living in the households of pensioners | -0.009 | Percentage point | NS | | | | | | Males 17-51 living in the households of pensioners | -0.051 | Percentage point | 5% | | 3 | Bacarreza and Vazquez-Ruiz (2013) | SP (Comer es primero component) (Dominican Republic) | Whether working | Men | 0.017 | Percentage point | NS | | | | SP (Comer es primero component) (Dominican Republic) | Whether working | Women | 0.047 | Percentage point | NS | | | | SP (ILEA component) (Dominican Republic) | Whether working | Men | 0.012 | Percentage point | NS | | | | SP (ILEA component) (Dominican Republic) | Whether working | Women | 0.018 | Percentage point | NS | | 4 | Barrientos and Villa (2013) | Familias en Acción (Colombia) | Whether working | Single female adults with children aged 0-6 years (urban) | 0.105 | Percentage point | 1% | | | | Familias en Acción (Colombia) | Whether working | Male adults 21-35 years old (urban) | 0.079 | Percentage point | 1% | | 5 | Behrman and Parker (2013) | PROGRESA / Oportunidades (Mexico) | Proportion working in the previous week in activity contributing to family income (5.5 years of exposure) | Women aged 50 and older | 0.101 | Percentage point | 1% | | | | PROGRESA / Oportunidades (Mexico) | Proportion working in the previous week in activity contributing to family income (5.5 years of exposure) | Men aged 50 and older | 0.037 | Percentage point | 10% | | | | PROGRESA / Oportunidades (Mexico) | Proportion working in the previous week in activity contributing to family income (5.5 years of exposure) | Women (50-59 pre-programme) | 0.109 | Percentage point | 1% | | | | PROGRESA / Oportunidades (Mexico) | Proportion working in the previous week in activity contributing to family income (5.5 years of exposure) | Women (60-69 pre-programme) | 0.118 | Percentage point | 5% | | | | PROGRESA / Oportunidades (Mexico) | Proportion working in the previous week in activity contributing to family income (5.5 years of exposure) | Women (70 and older pre-programme) | 0.081 | Percentage point | 10% | | 6 | Benedetti et al. (2015) | PRAF (Honduras) | Worked more than 1 hour in past week | Male (21-65 at baseline) | -0.001 | Percentage point | NS | | | | PRAF (Honduras) | Worked more than 1 hour in past week | Female (21-65 at baseline) | -0.002 | Percentage point | NS | | 7 | Cheema et al. (2014) | BISP (Pakistan) | Proportion of working age adults (19-64) engaged in economically productive activities | Female | 0.0000106 | Percentage point | NS | | 8 | Daidone et al. (2014a) | LCGP (Lesotho) | Participation in any labour activity in last 12 months | Adult men | -0.055 | Percentage point | NS | | | | LCGP (Lesotho) | Participation in any labour activity in last 12 months | Elderly men | 0.038 | Percentage point | NS |

Continued on next page

### Table A5.5.1 Summary of results for overall cash transfer effect on adult labour participation – by gender

| # | Study | Programme and country | Outcome variable | Treatment population | Effect | Measure of change | Significance | |----|--------------------------------------------|-----------------------|-------------------------------------------------------|----------------------|--------|-------------------|--------------| | 8 | Daidone et al. (2014a) | LCGP (Lesotho) | Participation in any labour activity in last 12 months | Adult women | 0.079 | Percentage point | 10% | | | | | | Elderly women | 0.004 | Percentage point | NS | | 9 | Ferro and Nicollela (2007) | Bolsa Escola/Bolsa Familia (Brazil) | Whether working | Urban females (mothers) | 0.007 | Percentage point | NS | | | | | | Rural females (mothers) | -0.002 | Percentage point | NS | | | | | | Urban males (fathers) | 0.006 | Percentage point | NS | | | | | | Rural males (fathers) | -0.004 | Percentage point | NS | | 10 | Galiani and McEwan (2013) | PRAF (Honduras) | Works outside the home | Adult women | 0.008 | Percentage point | NS | | | | | | Adult men | -0.013 | Percentage point | NS | | 11 | Novella et al. (2012) | PRAF (Honduras) | Whether working | Female (mothers) | 0.015 | Percentage point | NS | | | | | | Male (fathers) | -0.007 | Percentage point | NS | | | | PROGRESA (Mexico) | Whether working | Female (mothers) | -0.028 | Percentage point | 5% | | | | | | Male (fathers) | -0.002 | Percentage point | NS | | | | RPS (Nicaragua) | Whether working | Female (mothers) | -0.009 | Percentage point | NS | | | | | | Male (fathers) | -0.013 | Percentage point | NS | | 12 | Parker and Skoufias (2000) | PROGRESA (Mexico) | Whether working | Women (18-24) | 0 | Percentage point | NS | | | | PROGRESA (Mexico) | Whether working | Women (25-34) | -0.009 | Percentage point | NS | | | | PROGRESA (Mexico) | Whether working | Women (35-44) | -0.012 | Percentage point | NS | | | | PROGRESA (Mexico) | Whether working | Women (45-54) | -0.005 | Percentage point | NS | | | | PROGRESA (Mexico) | Whether working | Women (55+) | 0.037 | Percentage point | 5% | | | | PROGRESA (Mexico) | Whether working | Men (18-24) | 0.026 | Percentage point | NS | | | | PROGRESA (Mexico) | Whether working | Men (25-34) | 0.012 | Percentage point | NS | | | | PROGRESA (Mexico) | Whether working | Men (35-44) | 0.017 | Percentage point | 10% | | | | PROGRESA (Mexico) | Whether working | Men (45-54) | 0.021 | Percentage point | 10% | | | | PROGRESA (Mexico) | Whether working | Men (55+) | 0.01 | Percentage point | NS | | 13 | Rubio-Codina (2009) | Oportunidades (Mexico) | Participated in any work | Women | -0.008 | Percentage point | NS | | | | | | Men | -0.007 | Percentage point | NS | | 14 | Siaplay (2012) | SA-OAP (South Africa) | Whether working | Female (21-26) | 0.038 | Percentage point | NS | | | | | | Male (21-26) | -0.088 | Percentage point | NS | | 15 | Skoufias et al. (2013) | PAL (Mexico) | Having worked over previous week (paid or unpaid) or had work but did not work | Female (18-50 at baseline) | 0.02 | Percentage point | NS | | | | | | Male (18-50 at baseline) | 0.013 | Percentage point | NS | | 16 | Skoufias and Di Maro (2008) | PROGRESA (Mexico) | Worked in labour market in last week (if worked at all, paid or unpaid) (Oct 98) | Males | -0.03 | Percentage point | NS | | 17 | Teixeira (2010) | Bolsa Familia (Brazil) | Whether working | Male | -0.005 | Percentage point | NS | | | | | | Female | 0 | Percentage point | NS |

Notes: results represent all overall results reported and do not include those disaggregated by gender or showing the effect of variations in design features. Figures in bold indicate statistically significant. NS means the study did not find a statistically significant result, typically up to the 10% significance level.

### Table A5.5.2 Summary of results for overall cash transfer effect on intensity of adult work – by gender

| # | Study | Programme and country | Outcome variable | Treatment population | Effect | Measure of change | Significance | |----|--------------------------------|-----------------------|------------------|----------------------|--------|-------------------|-------------| | 1 | Alzua et al. (2013) | PRAF (Honduras) | No. of hours worked (among those working) | Female | 1.84 | Hours per week | NS | | | | | | Male | 0.493 | Hours per week | NS | | | | RPS (Nicaragua) | No. of hours worked (among those working) | Female | -5.668 | Hours per week | NS | | | | | | Male | -1.475 | Hours per week | NS | | | | PROGRESA (Mexico) | No. of hours worked (among those working) | Female | 0.184 | Hours per week | 10% | | | | | | Male | -0.015 | Hours per week | NS | | 2 | Asfaw et al. (2014) | OVC-CT (Kenya) | Days worked per year | Female (over 18) | -13.91 | Days per year | NS | | | | | | Male (over 18) | -18.582 | Days per year | NS | | 3 | Buser et al. (2014) | BOH (Ecuador) | No. of hours worked | Females (mothers) | -2.195 | “Hours worked” | NS | | 4 | Blattman et al. (2012) | YDP (Uganda) | Hours spent on all economic activities in past 4 weeks (differential impact compared to men) | Women | 6.36 | Hours per month | NS | | | | | | Men | 17.60 | Hours per month | 5% | | 5 | Blattman et al. (2013) | YDP (Uganda) | No. of hours worked per month (after 4 years) | Male | 18.76 | Hours per month | 5% | | | | | | Female | 38.13 | Hours per month | 1% | | 6 | Ferro and Nicollela (2007) | Bolsa Escola / Bolsa Familia (Brazil) | No. of hours worked | Female (mothers) urban | 1.455 | Hours per week | 5% | | | | | | Female (mothers) rural | -1.842 | Hours per week | 1% | | | | | | Male (fathers) urban | -0.635 | Hours per week | 5% | | | | | | Male (fathers) rural | -0.789 | Hours per week | NS | | 7 | Novella et al. (2012) | PRAF (Honduras) | No. of hours worked | Female | -1.156 | Hours per week | NS | | | | | | Male | 0.727 | Hours per week | NS | | | | PROGRESA (Mexico) | No. of hours worked | Female | 0.064 | Hours per week | NS | | | | | | Male | 2.137 | Hours per week | 5% | | | | RPS (Nicaragua) | No. of hours worked | Female | -3.627 | Hours per week | NS | | | | | | Male | -2.918 | Hours per week | 1% | | 8 | Ospina (2010) | Familias en Acción (Colombia) | Hours spent on paid work | Males (18-60) | 0.889 | Hours in previous day | 1% | | | Ospina (2010) | Familias en Acción (Colombia) | Hours spent on paid work | Females (18-60) | 0.174 | Hours in previous day | NS | | 9 | Rubio-Codina (2009) | Oportunidades (Mexico) | Number of hours worked in all work | Women | 0.052 | Hours in previous day | NS | | | Rubio-Codina (2009) | Oportunidades (Mexico) | Number of hours worked in all work | Men | -0.141 | Hours in previous day | 5% | | 10 | Teixeira (2010) | Bolsa Familia (Brazil) | No. of hours worked | Females | -1.184 | Hours per week | 5% | | | Teixeira (2010) | Bolsa Familia (Brazil) | No. of hours worked | Males | -0.555 | Hours per week | 5% |

Notes: results represent all overall results reported and do not include those disaggregated by gender or showing the effect of variations in design features. Figures in bold indicate statistically significant. NS means the study did not find a statistically significant result, typically up to the 10% significance level.

### Table A5.5.3 Summary of results for overall cash transfer effect on adult labour force participation – by sector and gender

| # | Study | Programme and country | Female / Male | Age | Outcome variable | Effect | Measure of change | Significance | |----|--------------------------------------------|-----------------------|---------------|-----------|-------------------------------------------------------|--------|-------------------|--------------| | 1 | Alzua et al. (2013) | PRAF (Honduras) | Female | Working in agricultural occupation | -0.036 | Percentage points | NS | | | | | Male | Working in agricultural occupation | -0.03 | Percentage points | NS | | | | RPS (Nicaragua) | Female | Working in agricultural occupation | -0.037 | Percentage points | NS | | | | | Male | Working in agricultural occupation | -0.002 | Percentage points | NS | | | | PROGRESA (Mexico) | Female | Working in agricultural occupation | -0.031 | Percentage points | NS | | | | | Male | Working in agricultural occupation | 0.016 | Percentage points | NS | | 2 | Asfaw et al. (2014) | OVC-CT (Kenya) | Female > 18 | Participation in own farm labour | 0.007 | Percentage point | NS | | | | | Male > 18 | Participation in own farm labour | -0.055 | Percentage point | NS | | 3 | Daidone et al. (2014a) | LCGP (Lesotho) | Male adult | Participation last 12m own non-farm business | 0.012 | Percentage point | NS | | | | | Male adult | Participation last 12m own agricultural activities | 0.027 | Percentage point | NS | | | | | Male adult | Participation last 12m paid work outside household | -0.087 | Percentage point | 1% | | | | | Female adult | Participation last 12m own non-farm business | -0.015 | Percentage point | NS | | | | | Female adult | Participation last 12m own agricultural activities | 0.067 | Percentage point | NS | | | | | Female adult | Participation last 12m paid work outside household | -0.03 | Percentage point | NS | | | | | Female elderly female | Participation last 12m own non-farm business | -0.103 | Percentage point | 5% | | | | | Female elderly female | Participation last 12m own agricultural activities | 0.107 | Percentage point | 10% | | | | | Female elderly female | Participation last 12m paid work outside household | -0.004 | Percentage point | NS | | | | | Female elderly female | Participation last week Own non-farm business | -0.034 | Percentage point | NS | | | | | Female elderly female | Participation last week Own crop & livestock production | 0.141 | Percentage point | 10% | | | | | Female elderly female | Participation last week paid work outside household | -0.066 | Percentage point | NS | | 4 | Galiani and McEwan (2013) | PRAF (Honduras) | Female 21-65 | Works outside the home | 0.008 | Percent point change | NS | | | | | Female 21-65 | Only works inside the home | -0.009 | Percent point change | NS | | | | | Male 21-65 | Works outside the home | -0.013 | Percent point change | NS | | | | | Male 21-65 | Only works inside the home | 0.008 | Percent point change | 10% | | 5 | Parker and Skoufias (2000) | PROGRESA (Mexico) | Female 18-24 | Probability of working – salaried work | -0.003 | % point from pre-programme level | NS | | | | | Female 25-34 | Probability of working – salaried work | 0.008 | % point from pre-programme level | NS | | | | | Female 35-44 | Probability of working – salaried work | -0.003 | % point from pre-programme level | NS | | | | | Female 45-54 | Probability of working – salaried work | 0.008 | % point from pre-programme level | NS |

*continued on next page*

### Table A5.5.3 Summary of results for overall cash transfer effect on adult labour force participation – by sector and gender continued

| # | Study | Programme and country | Female / Male | Age | Outcome variable | Effect | Measure of change | Significance | |----|--------------------------------------------|-----------------------|---------------|-----------|-------------------------------------------------------|---------|-------------------|--------------| | 5 | Parker and Skoufias (2000) | PROGRESA (Mexico) | Female | 55+ | Probability of working – salaried work | 0.015 | % point from pre-programme level | 10% | | | PROGRESA (Mexico) Female 18-24 | | | | Probability of working – self-employed/family business | 0.012 | % point from pre-programme level | NS | | | PROGRESA (Mexico) Female 25-34 | | | | Probability of working – self-employed/family business | 0.014 | % point from pre-programme level | NS | | | PROGRESA (Mexico) Female 35-44 | | | | Probability of working – self-employed/family business | 0.007 | % point from pre-programme level | NS | | | PROGRESA (Mexico) Female 45-54 | | | | Probability of working – self-employed/family business | 0 | % point from pre-programme level | NS | | | PROGRESA (Mexico) Female 55+ | | | | Probability of working – self-employed/family business | 0.021 | % point from pre-programme level | NS | | 6 | Skoufias et al. (2013) | PAL (Mexico) | Female | 18-60 in the baseline round; rural | Probability of working in AGRICULTURAL ACTIVITIES – FEMALE | -0.006 | Percentage point | NS | | | PAL (Mexico) Female 18-60 in the baseline round; rural | Probability of working in NON- AGRICULTURAL ACTIVITIES – FEMALE | 0.026 | Percentage point | NS | | | PAL (Mexico) Male 18-60 in the baseline round; rural | Probability of working in AGRICULTURAL ACTIVITIES – MALE | -0.05 | Percentage point | 5% | | | PAL (Mexico) Male 18-60 in the baseline round; rural | Probability of working in NON- AGRICULTURAL ACTIVITIES – MALE | 0.063 | Percentage point | 1% | | 7 | Skoufias and Di Maro (2008) | PROGRESA (Mexico) | Male | 18-55+ | Worked in labour market in last week – Salaried work (Nov 99) | 0.025 | % point from pre-programme level | NS | | | PROGRESA (Mexico) Male 18-55+ | | | | Worked in labour market in last week – self-employed / family business (Nov 99) | -0.007 | % point from pre-programme level | NS | | | PROGRESA (Mexico) Female 18-55+ | | | | Worked in labour market in last week – Salaried work (Nov 99) | 0.001 | % point from pre-programme level | NS | | | PROGRESA (Mexico) Female 18-55+ | | | | Worked in labour market in last week – self-employed / family business (Nov 99) | 0 | % point from pre-programme level | NS |

Note: When studies report results for last 12 months and last week/shorter time span, reporting working/not working and hours over last 12 months. Skoufias and Di Maro (2008) results disaggregated by age are also mostly non-significant. Figures in bold indicate statistically significant. NS means the study did not find a statistically significant result, typically up to the 10% significance level.

### Table A5.5.4 Summary of results for overall cash transfer effect on adult work intensity – by sector and gender

| # | Study | Programme and country | Female/ Male | Age | Outcome variable | Effect | Measure of change | Significance | |----|--------------------------------------------|-----------------------|--------------|-----|----------------------------------------------------------------------------------|--------|-------------------|-------------| | 1 | Asfaw et al. (2014) | OVC-CT (Kenya) | Female | > 18| Days worked per month in own farm labour | 0.406 | Days per year | NS | | | | OVC-CT (Kenya) | Male | > 18| Days worked per month in own farm labour | -0.622 | Days per year | NS | | 2 | Blattman et al. (2012) | YOP (Uganda) | Female | | Hours spent on market activities in past 4 weeks (differential effect compared to men) | 5.328 | Hours | NS | | | | YOP (Uganda) | Male | | Hours spent on market activities in past 4 weeks | 20.473 | Hours | 1% | | 3 | Daidone et al. (2014a) | LCGP (Lesotho) | Male | Adult| Hours worked last week own non-farm enterprise | 0.5 | hours | 10% | | | | LCGP (Lesotho) | Male | Adult| Hours worked last week Own crop & livestock | -1.9 | hours | NS | | | | LCGP (Lesotho) | Male | Adult| Hours worked last week paid labour | -5.2 | hours | 5% | | | | LCGP (Lesotho) | Female | Adult| hours worked last week own non-farm enterprise | -0.4 | hours | NS | | | | LCGP (Lesotho) | Female | Adult| hours worked last week Own crop & livestock | -0.5 | hours | NS | | | | LCGP (Lesotho) | Female | Adult| hours worked last week Paid labour | -1.2 | hours | NS | | | | LCGP (Lesotho) | Female | Elderly female| hours worked last week own non-farm enterprise | -2.5 | hours | 10% | | | | LCGP (Lesotho) | Female | Elderly female| hours worked last week Own crop & livestock | 3.6 | hours | 5% | | | | LCGP (Lesotho) | Female | Elderly female| hours worked last week Paid labour | -1.9 | hours | NS | | 4 | Handa et al. (2014) | LEAP (Ghana) | Male | | Number of days on own farm activity over last season | 7.7 | days | 10% | | | | LEAP (Ghana) | Female | | Number of days on own farm activity over last season | 6.1 | days | NS | | 5 | Ospina (2010) | Familias en Accion (Colombia) | Male | 18 to 60 | Hours spent on domestic labour | -0.406 | 1% | | | | Familias en Accion (Colombia) | Male | 18 to 60 | Hours spent on paid work | 0.889 | 1% | | | | Familias en Accion (Colombia) | Female | 18 to 60 | Hours spent on domestic labour | 0.274 | 10% | | | | Familias en Accion (Colombia) | Female | 18 to 60 | Hours spent on paid work | 0.174 | NS | | 6 | Rubio-Codina, M. (2009) | PROGRESA/Oportunidades (Mexico) | Women | All | Number of hours worked in market work | 0.104 | Hours | NS | | | | PROGRESA/Oportunidades (Mexico) | Men | All | Number of hours worked in market work | -0.06 | Hours | NS | | | | PROGRESA/Oportunidades (Mexico) | Women | All | Number of hours worked in farm work | 0.012 | Hours | NS | | | | PROGRESA/Oportunidades (Mexico) | Men | All | Number of hours worked in farm work | -0.025 | Hours | NS | | | | PROGRESA/Oportunidades (Mexico) | Women | All | Number of hours worked in domestic work | 0.046 | Hours | 5% | | | | PROGRESA/Oportunidades (Mexico) | Men | All | Number of hours worked in domestic work | -0.012 | Hours | NS | | | | PROGRESA/Oportunidades (Mexico) | Women | 18-24 | Number of hours worked in market work | -0.098 | Hours | NS | | | | PROGRESA/Oportunidades (Mexico) | Women | 25-34 | Number of hours worked in market work | 0.050 | Hours | NS |

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### Table A5.5.4 Summary of results for overall cash transfer effect on adult work intensity – by sector and gender continued

| # | Study | Programme and country | Female/ Male | Age | Outcome variable | Effect | Measure of change | Significance | |----|--------------------------------------------|-----------------------|--------------|-------|-----------------------------------|--------|-------------------|--------------| | 6 | Rubio-Codina, M. (2009) | PROGRESA/ Oportunidades (Mexico) | Women | 35-44 | Number of hours worked in market work | 0.214 | Hours | NS | | | PROGRESA/ Oportunidades (Mexico) | Women | 45-54 | | Number of hours worked in market work | 0.485 | Hours | NS | | | PROGRESA/ Oportunidades (Mexico) | Women | 55+ | | Number of hours worked in market work | 0.265 | Hours | NS | | | PROGRESA/ Oportunidades (Mexico) | Women | 18-24 | | Number of hours worked in farm work | 0.006 | Hours | NS | | | PROGRESA/ Oportunidades (Mexico) | Women | 25-34 | | Number of hours worked in farm work | 0.021 | Hours | NS | | | PROGRESA/ Oportunidades (Mexico) | Women | 35-44 | | Number of hours worked in farm work | 0.028 | Hours | NS | | | PROGRESA/ Oportunidades (Mexico) | Women | 45-54 | | Number of hours worked in farm work | -0.022 | Hours | NS | | | PROGRESA/ Oportunidades (Mexico) | Women | 55+ | | Number of hours worked in farm work | 0.009 | Hours | NS | | | PROGRESA/ Oportunidades (Mexico) | Women | 18-24 | | Number of hours worked in domestic work | -0.158 | Hours | NS | | | PROGRESA/ Oportunidades (Mexico) | Women | 25-34 | | Number of hours worked in domestic work | 0.201 | Hours | 5% | | | PROGRESA/ Oportunidades (Mexico) | Women | 35-44 | | Number of hours worked in domestic work | 0.087 | Hours | NS | | | PROGRESA/ Oportunidades (Mexico) | Women | 45-54 | | Number of hours worked in domestic work | 0.044 | Hours | NS | | | PROGRESA/ Oportunidades (Mexico) | Women | 55+ | | Number of hours worked in domestic work | -0.005 | Hours | NS |

Figures in bold indicate statistically significant. NS means the study did not find a statistically significant result, typically up to the 10% significance level.

### Table A5.5.5 Summary of results for overall cash transfer effect on child labour participation — by gender

| # | Study | Programme and country | Outcome variable | Treatment population | Effect | Measure of change | Significance | |----|--------------------------------|-----------------------|-----------------------------------------------------------------------------------|----------------------|--------|-------------------|--------------| | 1 | Alam et al. (2011) | PFSSP (Pakistan) | Whether looking for a job or participating in work for pay or unpaid work (unpaid family helper and unpaid work outside the home) | Girls 12-19 years old | -0.049 | Percentage point | 5% | | | | PFSSP (Pakistan) | Whether looking for a job or participating in work for pay or unpaid work (unpaid family helper and unpaid work outside the home) | Girls 15-16 years old | 0.0401 | Percentage point | 5% | | 2 | Behrman et al. (2011) | PROGRESA / Oportunidades (Mexico) | Whether working in 2003 (after 5.5 years) | Girls 15-16 years old | 0.01 | Percentage point | NS | | | | PROGRESA / Oportunidades (Mexico) | Whether working in 2003 (after 5.5 years) | Girls 17-18 years old | -0.01 | Percentage point | NS | | | | PROGRESA / Oportunidades (Mexico) | Whether working in 2003 (after 5.5 years) | Girls 19-21 years old | 0.064 | Percentage point | 10% | | | | PROGRESA / Oportunidades (Mexico) | Whether working in 2003 (after 5.5 years) | Boys 15-16 years old | -0.14 | Percentage point | 1% | | | | PROGRESA / Oportunidades (Mexico) | Whether working in 2003 (after 5.5 years) | Boys 17-18 years old | 0.06 | Percentage point | NS | | | | PROGRESA / Oportunidades (Mexico) | Whether working in 2003 (after 5.5 years) | Boys 19-21 years old | -0.02 | Percentage point | NS | | 3 | Berhman et al. (2012) | Oportunidades (Mexico) | Employed for pay (after 2 years) | Boys 12-14 years old (urban) | -0.124 | Percentage point | 5% | | | | Oportunidades (Mexico) | Employed for pay (after 2 years) | Boys 15-18 years old (urban) | -0.051 | Percentage point | NS | | | | Oportunidades (Mexico) | Employed for pay (after 2 years) | Boys 19-20 years old (urban) | -0.154 | Percentage point | NS | | | | Oportunidades (Mexico) | Employed for pay (after 2 years) | Boys 6-20 years old (urban) | -0.103 | Percentage point | 5% | | | | Oportunidades (Mexico) | Employed for pay (after 2 years) | Girls 12-14 years old (urban) | -0.01 | Percentage point | NS | | | | Oportunidades (Mexico) | Employed for pay (after 2 years) | Girls 15-18 years old (urban) | 0.004 | Percentage point | NS | | | | Oportunidades (Mexico) | Employed for pay (after 2 years) | Girls 19-20 years old (urban) | 0.087 | Percentage point | NS | | | | Oportunidades (Mexico) | Employed for pay (after 2 years) | Girls 6-20 years old (urban) | 0.002 | Percentage point | NS | | 4 | Bustelo (2011) | RPS (Nicaragua) | Whether working | Girls 7-13 years old (with non-targeted siblings) | -0.075 | Percentage point | NS | | | | RPS (Nicaragua) | Whether working | Boys 7-13 years old (with non-targeted siblings) | -0.074 | Percentage point | NS | | 5 | Cheema et al (2014) | BISP (Pakistan) | Proportion of boys aged 5-14 years engaged in child labour | Boys 5-14 years old | -0.04538 | Percentage point | 5% | | | | | Proportion of girls aged 5-14 years engaged in child labour | Girls 5-14 years old | -0.01066 | Percentage point | NS | | 6 | Daidone et al. (2014a) | LCGP (Lesotho) | Participation in any labour activity in past 12 months | Boys | -0.016 | Percentage point | NS | | | | LCGP (Lesotho) | Participation in any labour activity in past 12 months | Girls | -0.012 | Percentage point | NS | | 7 | Daidone et al. (2014b) | ZCGP (Zambia) | Total child labour supply (share) | Boys | 0.083 | Percentage point | NS | | | | ZCGP (Zambia) | Total child labour supply (share) | Girl | 0.016 | Percentage point | NS | | 8 | Dammert (2008) | Atención a Crisis (Nicaragua) | Participation in labour activities (2002) | Boys 7-13 years old (at baseline) | -0.138 | Percentage point | 5% | | | | Atención a Crisis (Nicaragua) | Participation in labour activities (2002) | Girls 7-13 years old (at baseline) | -0.014 | Percentage point | NS | | | | Atención a Crisis (Nicaragua) | Participation in labour activities (2001) | Children 7-13 at baseline (male-headed households) | 0.076 | Percentage points | 10% |

*continued on next page*

### Table A5.5.5 Summary of results for overall cash transfer effect on child labour participation — by gender

| # | Study | Programme and country | Outcome variable | Treatment population | Effect | Measure of change | Significance | |----|------------------------------|-----------------------|------------------|--------------------------------------------------------------------------------------|--------|-------------------|--------------| | 8 | Dammert (2008) | Atención a Crisis (Nicaragua) | Participation in labour activities (2001) | Children 7-13 at baseline (female-headed households) | -0.131 | Percentage points | 5% | | | | Atención a Crisis (Nicaragua) | Participation in labour activities (2002) | Children 7-13 at baseline (male-headed households) | 0.005 | Percentage points | NS | | | | Atención a Crisis (Nicaragua) | Participation in labour activities (2002) | Children 7-13 at baseline (female-headed households) | -0.082 | Percentage points | NS | | 9 | Edmonds and Schady (2008) | BDH (Ecuador) | Working for pay | Girls | -0.0910| Percentage point | NS | | | | BDH (Ecuador) | Working for pay | Boys | -0.0140| Percentage point | NS | | 10 | Ferro and Nicolella (2007) | Bolsa Escola / Bolsa Familia (Brazil) | Whether working | Girls 6-10 years old (urban) | -0.006 | Percentage point | 1% | | | | Bolsa Escola / Bolsa Familia (Brazil) | Whether working | Girls 6-10 years old (rural) | -0.04 | Percentage point | 5% | | | | Bolsa Escola / Bolsa Familia (Brazil) | Whether working | Girls 11-15 years old (urban) | -0.016 | Percentage point | NS | | | | Bolsa Escola / Bolsa Familia (Brazil) | Whether working | Girls 11-15 years old (rural) | -0.129 | Percentage point | 1% | | | | Bolsa Escola / Bolsa Familia (Brazil) | Whether working | Boys 6-10 years old (urban) | -0.003 | Percentage point | NS | | | | Bolsa Escola / Bolsa Familia (Brazil) | Whether working | Boys 6-10 years old (rural) | -0.032 | Percentage point | NS | | | | Bolsa Escola / Bolsa Familia (Brazil) | Whether working | Boys 11-15 years old (urban) | -0.048 | Percentage point | 1% | | | | Bolsa Escola / Bolsa Familia (Brazil) | Whether working | Boys 11-15 years old (rural) | -0.06 | Percentage point | NS | | 11 | Gallani and McEwan (2013) | PRAF (Honduras) | Works outside the home | Girls | -0.006 | Percentage point | NS | | | | PRAF (Honduras) | Works outside the home | Boys | -0.007 | Percentage point | NS | | 12 | Lincove and Parker (2015) | RPS (Nicaragua) | Work participation | Boys 6-11 years old (always eligible) | -0.05 | Percentage point | NS | | | | RPS (Nicaragua) | Work participation | Boys 12-13 years old (sometimes eligible) | -0.198 | Percentage point | 1% | | | | RPS (Nicaragua) | Work participation | Girls 6-11 years old (always eligible) | -0.027 | Percentage point | NS | | | | RPS (Nicaragua) | Work participation | Girls 12-13 years old (sometimes eligible) | -0.046 | Percentage point | NS | | 13 | Maluccio (2005) | RPS (Nicaragua) | Working (2 years after baseline) | Girls 7-12 years old | 0.0553 | Percentage point | 10% | | | | RPS (Nicaragua) | Working (2 years after baseline) | Boys 7-12 years old | -0.0175| Percentage point | NS | | 14 | Merttens et al. (2015) | SAGE Senior Citizen Grant (Uganda) | Proportion engaged in labour | Boys 6-17 years old | -0.07 | Proportion | NS | | | | SAGE Senior Citizen Grant (Uganda) | Proportion engaged in labour | Girls 6-17 years old | 0 | Proportion | NS | | | | SAGE Vulnerable Family Support Grant (Uganda) | Proportion engaged in labour | Boys 6-17 years old | 0.03 | Proportion | NS | | | | SAGE Vulnerable Family Support Grant (Uganda) | Proportion engaged in labour | Girls 6-17 years old | -0.02 | Proportion | NS | | 15 | Miller et al. (2011) | SCTP (Malawi) | Doing any income-generating activity | Girls | -0.1 | Percentage point | 1% | | | | SCTP (Malawi) | Doing any income-generating activity | Boys | -0.12 | Percentage point | 1% | | 16 | Parker and Skoufas (2000) | PROGRESA (Mexico) | Whether working | Girls 8-17 years old | -0.013 | Percentage points | 10% |

continued on next page

### Table A5.5.5 Summary of results for overall cash transfer effect on child labour participation – by gender continued

| # | Study | Programme and country | Outcome variable | Treatment population | Effect | Measure of change | Significance | |----|--------------------------------------------|-----------------------|------------------|----------------------|--------|-------------------|--------------| | 16 | Parker and Skoufias (2000) | PROGRESA (Mexico) | Whether working | Girls 12-13 years old | -0.009 | Percentage points | NS | | | | | | Girls 14-15 years old | -0.039 | Percentage points | 5% | | | | | | Girls 16-17 years old | 0.012 | Percentage points | NS | | | | | | Boys 8-17 years old | -0.031 | Percentage points | 5% | | | | | | Boys 12-13 years old | -0.041 | Percentage points | 5% | | | | | | Boys 14-15 years old | -0.054 | Percentage points | 10% | | | | | | Boys 16-17 years old | 0.025 | Percentage points | NS | | 17 | Rubio-Codina (2009) | Oportunidades (Mexico)| Participation in all work | Girls | -0.015 | Percentage point | NS | | | | | | Boys | -0.014 | Percentage point | NS | | | | | | Girls 9-11 years old | 0.001 | Percentage point | NS | | | | | | Girls 12-17 years old| -0.028 | Percentage point | NS | | 18 | Sadoulet et al. (2004) | PROGRESA (Mexico) | Whether worked in previous week | Girls 11 years old at baseline | -0.04 | Percentage points | 1% | | | | | | Girls 12-14 years old at baseline | -0.066 | Percentage points | 1% | | | | | | Girls 15-17 years old at baseline | -0.004 | Percentage points | NS | | | | | | Boys 11 years old at baseline | -0.05 | Percentage points | 1% | | | | | | Boys 12-14 years old at baseline | -0.073 | Percentage points | 1% | | | | | | Boys 15-17 years old at baseline | -0.043 | Percentage points | NS | | 19 | Schultz (2004) | PROGRESA (Mexico) | Participation in paid work | Girls (primary school age) | -0.004 | Percentage point | 5% | | | | | | Boys (primary school age) | -0.0179| Percentage point | 5% | | | | | | Girls (secondary school age) | -0.0527| Percentage point | 5% | | | | | | Boys (secondary school age) | -0.101 | Percentage point | 5% | | 20 | Stapley (2012) | SA-OAP (South Africa) | Whether employed or not | Female 14-20 years old | -0.032 | Percentage point | NS | | | | | | Male 14-20 years old | -0.025 | Percentage point | NS | | 21 | Skoufias and Parker (2001) | PROGRESA (Mexico) | Whether working | Girls 8-11 years old | 0 | Percentage point | NS | | | | | | Girls 12-17 years old | -0.023 | Percentage point | 10% | | | | | | Boys 8-11 years old | -0.011 | Percentage point | NS | | | | | | Boys 12-17 years old | -0.047 | Percentage point | 5% |

Notes: results represent all overall results reported and do not include those disaggregated by gender or showing the effect of variations in design features. Figures in bold indicate statistically significant. NS means the study did not find a statistically significant result, typically up to the 10% significance level.

### Table A5.5.6 Summary of results for overall cash transfer effect on intensity of child labour – by gender

| # | Study | Programme and country | Outcome variable | Treatment population | Effect | Measure of change | Significance | |----|------------------------------|-----------------------|------------------|----------------------|--------|-------------------|--------------| | 1 | Alam et al. (2011) | PFSSP (Pakistan) | Days per month | Girls 12-19 years old | -0.548 | Days per month | NS | | | | PFSSP (Pakistan) | Days per month | Girls 15-16 years old | -6.137 | Days per month | 10% | | 2 | Barrera-Osorio et al. (2008) | SCAE (Colombia) | No. of hours worked last week | Girls | -0.378 | Hours per week | 5% | | | | SCAE (Colombia) | No. of hours worked last week | Boys | -0.619 | Hours per week | 5% | | 3 | Dammert (2008) | Atención a Crisis (Nicaragua) | Hours worked (2001) | Boys 7-13 years old (at baseline) | -20.42 | ‘Hours worked’ | NS | | | | Atención a Crisis (Nicaragua) | Hours worked (2001) | Girls 7-13 years old (at baseline) | -12.335 | ‘Hours worked’ | NS | | | | Atención a Crisis (Nicaragua) | Hours worked (2002) | Boys 7-13 years old (at baseline) | -19.11 | ‘Hours worked’ | NS | | | | Atención a Crisis (Nicaragua) | Hours worked (2002) | Girls 7-13 years old (at baseline) | -11.778 | ‘Hours worked’ | NS | | | | Atención a Crisis (Nicaragua) | Hours worked (2001) | Children 7-13 at baseline (male headed) | 35.752 | Hours | 5% | | | | Atención a Crisis (Nicaragua) | Hours worked (2001) | Children 7-13 at baseline (female headed) | -51.84 | Hours | 10% | | | | Atención a Crisis (Nicaragua) | Hours worked (2002) | Children 7-13 at baseline (male headed) | -1.361 | Hours | NS | | | | Atención a Crisis (Nicaragua) | Hours worked (2002) | Children 7-13 at baseline (female headed) | -16.191 | Hours | NS | | 4 | Del Carpio and Macours (2009) | Atención a Crisis – cash transfer only (Nicaragua) | No. of hours worked per week (all work) | Girls 6-15 years old | -0.747 | Hours per week | NS | | | | | No. of hours worked per week (all work) (difference compared to beneficiary girls) | Boys 6-15 years old | -0.1478 | Hours per week | 5% | | | | | No. of hours worked per week (all work) (difference compared to younger beneficiary girls) | Girls 6-9 years old | -1.208 | Hours per week | 5% | | | | | No. of hours worked per week (all work) (difference compared to younger beneficiary girls) | Girls 10-15 years old | 0.805 | Hours per week | NS | | | | | No. of hours worked per week (all work) (compared to younger girls) | Boys 6-9 years old | -0.489 | Hours per week | NS | | | | | No. of hours worked per week (all work) (compared to younger boys) | Boys 10-15 years old | -3.011 | Hours per week | 1% | | | | | No. of hours worked per week (all work) (compared to younger boys) | Boys 6-9 years old | 0.241 | Hours per week | NS | | | | | No. of hours worked per week (all work) (compared to younger boys) | Boys 10-15 years old | -3.503 | Hours per week | 1% | | 5 | Del Carpio and Loayza (2012) | Atención a Crisis (Nicaragua) | No. of hours worked per child in the past week | Boys | -1.773 | Hours per week | 1% | | | | Atención a Crisis (Nicaragua) | No. of hours worked per child in the past week | Girls | -1.212 | Hours per week | 1% | | 6 | Ferro and Nicolella (2007) | Conditional educational transfers, principally Bolsa Escola (Brazil) | No. of hours spent on work per week | Girls 6-10 years old (urban) | -0.582 | Hours per week | NS | | | | | No. of hours spent on work per week | Girls 6-10 years old (rural) | -1.001 | Hours per week | NS | | | | | No. of hours spent on work per week | Girls 11-15 years (urban) | -1.834 | Hours per week | NS | | | | | No. of hours spent on work per week | Girls 11-15 years (rural) | -0.691 | Hours per week | NS | | | | | No. of hours spent on work per week | Boys 6-10 years (urban) | 0.222 | Hours per week | NS | | | | | No. of hours spent on work per week | Boys 6-10 years (rural) | -1.304 | Hours per week | NS |

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### Table A5.5.6 Summary of results for overall cash transfer effect on intensity of child labour – by gender

| # | Study | Programme and country | Outcome variable | Treatment population | Effect | Measure of change | Significance | |----|------------------------------|-----------------------|------------------|----------------------|--------|-------------------|--------------| | 6 | Ferro and Nicolella (2007) | As above | No. of hours spent on work per week | Boys 11-15 years old (urban) | -2.359 | Hours per week | 10% | | | | As above | No. of hours spent on work per week | Boys 11-15 years old (rural) | -0.432 | Hours per week | NS | | 7 | Lincove and Parker (2015) | RPS (Nicaragua) | No. of hours worked (paid or unpaid) | Boys 6-11 years old (always eligible) | -2.771 | Hours per week | 1% | | | | RPS (Nicaragua) | No. of hours worked (paid or unpaid) | Boys 12-13 years (sometimes eligible) | -8.734 | Hours per week | 1% | | | | RPS (Nicaragua) | No. of hours worked (paid or unpaid) | Girls 6-11 years old (always eligible) | -0.486 | Hours per week | 1% | | | | RPS (Nicaragua) | No. of hours worked (paid or unpaid) | Girls 12-13 years old (sometimes eligible) | -1.855 | Hours per week | NS | | 8 | Rubio-Codina (2009) | Oportunidades (Mexico) | No. of hours worked (all work) | Boys | -0.104 | Hours per day | 10% | | | | Oportunidades (Mexico) | No. of hours worked (all work) | Girls | -0.084 | Hours per day | 10% | | | | Oportunidades (Mexico) | No. of hours worked (all work) | Girls 9-11 years old | 0.01 | Hours per day | NS | | | | Oportunidades (Mexico) | No. of hours worked (all work) | Girls 12-17 years old | -0.145 | Hours per day | 5% |

Notes: results represent all overall results reported and do not include those disaggregated by gender or showing the effect of variations in design features. Figures in bold indicate statistically significant. NS means the study did not find a statistically significant result, typically up to the 10% significance level.

### Table A5.5.7 Summary of results for cash transfer effect on child labour participation – by sector and gender

| # | Study | Programme and country | Child age | Female/ Male | Outcome variable | Effect | Measure of change | Significance | |----|--------------------------------------------|-----------------------|-----------|--------------|-------------------------------------------------------|--------|-------------------|--------------| | 1 | Asfaw et al. (2014) | OVC-CT (Kenya) | 10 to 15 | Boys | participation in own farm labour by children | -0.120 | percentage points | 5% | | | | OVC-CT (Kenya) | 10 to 15 | Girls | participation in own farm labour by children | -0.072 | percentage points | NS | | 2 | Behrman et al. (2011) | PROGRESA / Oportunidades (Mexico) | 15-16 in 2003 | Female | Whether participating in agricultural work in 2003 | -0.004 | % point | NS | | | | PROGRESA / Oportunidades (Mexico) | 17-18 in 2003 | Female | Whether participating in agricultural work in 2004 | -0.02 | % point | NS | | | | PROGRESA / Oportunidades (Mexico) | 19-21 in 2003 | Female | Whether participating in agricultural work in 2005 | 0.01 | % point | NS | | 3 | Daidone et al. (2014a) | LCGP (Lesotho) | Boys | Participation last 12m own non-farm business | -0.003 | Percentage point | NS | | | | LCGP (Lesotho) | Boys | Participation last 12m own agricultural activities | -0.029 | Percentage point | NS | | | | LCGP (Lesotho) | Boys | Participation last 12m paid work outside household | -0.011 | Percentage point | NS | | | | LCGP (Lesotho) | Girls | Participation last 12m own non-farm business | 0.001 | Percentage point | NS | | | | LCGP (Lesotho) | Girls | Participation last 12m own agricultural activities | 0.008 | Percentage point | NS | | | | LCGP (Lesotho) | Girls | Participation last 12m paid work outside household | 0.011 | Percentage point | NS | | 4 | Daidone et al. (2014b) | ZCGP (Zambia) | 5-18 Boys | Paid child labour supply | -0.017 | Percentage point | NS | | | | ZCGP (Zambia) | 5-18 Boys | Unpaid child labour supply | 0.079 | Percentage point | NS | | | | ZCGP (Zambia) | 5-18 Girls | Paid child labour supply | -0.014 | Percentage point | NS | | | | ZCGP (Zambia) | 5-18 Girls | Unpaid child labour supply | 0.002 | Percentage point | NS | | 5 | Edmonds and Schady (2008) | BDH (Ecuador) | 10 and older Girls | Children 10 and older work for pay | -0.0910 | Percent point change | NS | | | | BDH (Ecuador) | 10 and older Girls | Children 10 and older do market work | -0.191 | Percent point change | 5% | | | | BDH (Ecuador) | 10 and older Girls | Children 10 and older do unpaid market work | -0.159 | Percent point change | 10% | | | | BDH (Ecuador) | 10 and older Girls | Children 10 and older do domestic work | 0.0569 | Percent point change | NS | | | | BDH (Ecuador) | 10 and older Boys | Children 10 and older work for pay | -0.0140 | Percent point change | NS | | | | BDH (Ecuador) | 10 and older Boys | Children 10 and older do market work | -0.0941 | Percent point change | 5% | | | | BDH (Ecuador) | 10 and older Boys | Children 10 and older do unpaid market work | 0.0778 | Percent point change | 1.05 | | | | BDH (Ecuador) | 10 and older Boys | Children 10 and older do domestic work | 0.0161 | Percent point change | NS | | 6 | Galliani and McEwan (2013) | PRAF (Honduras) | Girls | Only works inside the home | -0.035 | Percent point change | NS | | | | PRAF (Honduras) | Boys | Only works inside the home | -0.018 | Percent point change | NS | | 7 | Miller et al. (2011) | SCTP (Malawi) | Girls | Doing any work on chores | 0.11 | Percent point change | 1% | | | | SCTP (Malawi) | Boys | Doing any work on chores | 0.08 | Percent point change | 10% | | | | SCTP (Malawi) | Girls | Doing any work on family farm/ business | 0.01 | Percent point change | NS |

*continued on next page* Table A5.5.7 Summary of results for cash transfer effect on child labour participation – by sector and gender continued

| # | Study | Programme and country | Child age | Female/ Male | Outcome variable | Effect | Measure of change | Significance | |----|--------------------------------------------|-----------------------|-----------|--------------|----------------------------------------------------------------------------------|--------|------------------|--------------| | 7 | Miller et al. (2011) | SCTP (Malawi) | Boys | | doing any work on family farm/business | 0.09 | Percent point change | NS | | 8 | Parker and Skoufias (2000) | PROGRESA (Mexico) | age 8-17 | female | Impact of PROGRESA on the probability of working in – SALARIED WORK | -0.003 | % point from pre-programme level | NS | | | | | age 12-13 | female | Impact of PROGRESA on the probability of working in – SALARIED WORK | -0.007 | % point from pre-programme level | 10% | | | | | age 14-15 | female | Impact of PROGRESA on the probability of working in – SALARIED WORK | -0.016 | % point from pre-programme level | NS | | | | | age 16-17 | female | Impact of PROGRESA on the probability of working in – SALARIED WORK | -0.002 | % point from pre-programme level | NS | | | | | age 8-17 | female | The impact of PROGRESA on the probability of working in – SELF-EMPLOYED/FAMILY BUSINESS | -0.007 | % point from pre-programme level | NS | | | | | age 12-13 | female | The impact of PROGRESA on the probability of working in – SELF-EMPLOYED/FAMILY BUSINESS | -0.002 | % point from pre-programme level | NS | | | | | age 14-15 | female | The impact of PROGRESA on the probability of working in – SELF-EMPLOYED/FAMILY BUSINESS | -0.02 | % point from pre-programme level | 1% | | | | | age 16-17 | female | The impact of PROGRESA on the probability of working in – SELF-EMPLOYED/FAMILY BUSINESS | -0.007 | % point from pre-programme level | NS | | 9 | Schultz (2004) | PROGRESA (Mexico) | Primary school girls | Female | Work market and household | -0.148 | Percent point change | 5% | | | | | Primary school boys | Male | Work market and household | -0.188 | Percent point change | 5% | | | | | Secondary school girls | Female | Work market and household | -0.463 | Percent point change | 10% | | | | | Secondary school boys | Male | Work market and household | -0.389 | Percent point change | NS | | | | | Primary school girls | Female | Work market | -0.0258 | Percent point change | 10% | | | | | Primary school boys | Male | Work market | -0.12 | Percent point change | 5% | | | | | Secondary school girls | Female | Work market | -0.128 | Percent point change | 5% | | | | | Secondary school boys | Male | Work market | -0.28 | Percent point change | 5% | | 10 | Skoufias and Parker (2001) | PROGRESA (Mexico) | 8 to 17 | Female | PARTICIPATION in MARKET – GIRLS 8-17 | 0 | NS | | | | | | 12 to 17 | Female | PARTICIPATION in MARKET – GIRLS 12-17 | 0 | NS | | | | | | 8 to 17 | Female | PARTICIPATION in DOMESTIC – GIRLS 8-17 | -0.04 | 1% | | | | | | 12 to 17 | Female | PARTICIPATION in DOMESTIC – GIRLS 12-17 | -0.43 | 1% | | | | | | 8 to 17 | Female | PARTICIPATION in FARM – GIRLS 8-17 | 0 | NS | | | | | | 12 to 17 | Female | PARTICIPATION in FARM – GIRLS 12-17 | -0.004 | NS | |

### Table A5.5.8 Summary of results for cash transfer effect on child labour intensity – by sector and gender

| # | Study | Programme and country | Child age | Female/ Male | Outcome variable | Effect | Measure of change | Significance | |----|--------------------------------------------|-----------------------|-----------|--------------|----------------------------------------------------------------------------------|--------|-------------------|--------------| | 1 | Daidone et al. (2014a) | LCGP (Lesotho) | Boys | | hours worked last week own non farm enterprise | 0.1 | hours | NS | | | LCGP (Lesotho) | Boys | hours worked last week Own crop & livestock | -2.7 | hours | NS | | | LCGP (Lesotho) | Boys | hours worked last week Paid labour | -0.4 | hours | NS | | | LCGP (Lesotho) | Girls | hours worked last week own non farm enterprise | 0 | hours | NS | | | LCGP (Lesotho) | Girls | hours worked last week Own crop & livestock | -0.4 | hours | NS | | | LCGP (Lesotho) | Girls | hours worked last week Paid labour | 0.4 | hours | NS | | 2 | Del Carpio and Macours (2009) | Atención a Crisis | All Female | | Cash transfer only group Number of hours per week child worked in non-agricultural | 0.0864 | Hours per week | 5% | | | Atención a Crisis | All Male | Cash transfer only group Number of hours per week child worked in non-agricultural | 0.106 | Hours per week | 1% | | | Atención a Crisis | All Female | Cash transfer only group Number of hours per week child worked in agricultural | -0.269 | Hours per week | 1% | | | Atención a Crisis | All Male | Cash transfer only group Number of hours per week child worked in agricultural | 0.0501 | Hours per week | NS | | | Atención a Crisis | All Female | Cash transfer only group Number of hours per week child worked in domestic work | -0.399 | Hours per week | 10% | | | Atención a Crisis | All Male | Cash transfer only group Number of hours per week child worked in domestic work | -0.161 | Hours per week | 10% | | | Atención a Crisis | 10 to 15 Female | Cash transfer only group Number of hours per week child worked in non-agricultural | 0.181 | Hours per week | NS | | | Atención a Crisis | 6 to 15 Female | Cash transfer only group Number of hours per week child worked in non-agricultural | -0.288 | Hours per week | 5% | | | Atención a Crisis | 6 to 15 Female | Cash transfer only group Number of hours per week child worked in non-agricultural | 0.192 | Hours per week | 5% | | | Atención a Crisis | 10 to 15 Female | Cash transfer only group Number of hours per week child worked in agricultural | -0.0295 | Hours per week | NS | | | Atención a Crisis | 6 to 15 Female | Cash transfer only group Number of hours per week child worked in agricultural | 0.0735 | Hours per week | NS | | | Atención a Crisis | 10 to 15 Female | Cash transfer only group Number of hours per week child worked in agricultural | -0.399 | Hours per week | 10% | | 3 | Del Carpio, X. and Loayza, N. V. (2012) | Atención a Crisis | Female | | Number of hrs worked per child in the week previous to the survey – HOUSEHOLD CHORES | -1.085 | hours | 1% | | 4 | Ospina (2010) | Familias en Acción | 10 to 13 Boys | | Hours spent on paid work | 1.855 | NS | | | | Familias en Acción | 14 to 17 Boys | Hours spent on paid work | -1.408 | NS | 10% | | | Familias en Acción | 10 to 13 Boys | Hours spent on domestic work | -0.545 | NS | 1% | | | Familias en Acción | 14 to 17 Boys | Hours spent on domestic work | -0.524 | NS | 10% | | | Familias en Acción | 10 to 13 Girls | Hours spent on paid work | 0.045 | NS | | | | Familias en Acción | 14 to 17 Girls | Hours spent on paid work | -0.799 | NS | | | | Familias en Acción | 10 to 13 Girls | Hours spent on domestic work | -0.355 | NS | 5% | | | Familias en Acción | 14 to 17 Girls | Hours spent on domestic work | 0.195 | NS | |

*continued on next page*

### Table A5.5.8 Summary of results for cash transfer effect on child labour intensity – by sector and gender

| # | Study | Programme and country | Child age | Female/ Male | Outcome variable | Effect | Measure of change | Significance | |----|------------------------|-----------------------|-----------|--------------|-----------------------------------|--------|-------------------|--------------| | 5 | Rubio-Codina (2009) | PROGRESA / Oportunidades (Mexico) | Girls | Girls | Number of hours worked in market work | -0.097 | Marginal effect | NS | | | | | Boys | Boys | Number of hours worked in market work | -0.15 | Marginal effect | 10% | | | | | Aged 9-11| Girls | Number of hours worked in market work | 0.03 | Marginal effect | NS | | | | | Aged 12-17| Girls | Number of hours worked in market work | -0.121 | Marginal effect | NS | | | | | Girls | Girls | Number of hours worked in farm work | 0.043 | Marginal effect | NS | | | | | Boys | Boys | Number of hours worked in farm work | -0.035 | Marginal effect | NS | | | | | Aged 9-11| Girls | Number of hours worked in farm work | 0.085 | Marginal effect | NS | | | | | Aged 12-17| Girls | Number of hours worked in farm work | 0.014 | Marginal effect | NS | | | | | Girls | Girls | Number of hours worked in domestic work | -0.097 | Marginal effect | 5% | | | | | Boys | Boys | Number of hours worked in domestic work | -0.02 | Marginal effect | NS | | | | | Aged 9-11| Girls | Number of hours worked in domestic work | -0.028 | Marginal effect | NS | | | | | Aged 12-17| Girls | Number of hours worked in domestic work | -0.139 | Marginal effect | 1% | | 6 | World Bank (2011) | PKH (Indonesia) | 7 to 12 | Boys | Family enterprise work last week | 0.01 | Hours | NS | | | | | 13 to 15 | Boys | Family enterprise work last week | 3.03 | Hours | 1% | | | | | 7 to 12 | Girls | Family enterprise work last week | 4.77 | Hours | 1% | | | | | 13 to 15 | Girls | Family enterprise work last week | 2.14 | Hours | NS |

### Table A5.5.9 Summary of results for overall cash transfer effect on migration – by gender

| # | Study | Programme and country | Outcome indicator and treatment population | Effect | Measure of change | Significance | |----|------------------------|-----------------------|------------------------------------------------------------------------------------------------------------|--------|-------------------|--------------| | 1 | Ardington et al. (2009) | SA-OAP (South Africa) | Migrating internally (female members) | 0.051 | Percentage points | 5% | | | | SA-OAP (South Africa) | Migrating internally (male members) | 0.034 | Percentage points | 5% | | 2 | Behrman et al. (2009) | Oportunidades (Mexico)| Having migrated internally by 2003 compared to those started receiving programme two years later (girls 9-15 in 1997) | -0.09 | Percent point change | NS | | | | Oportunidades (Mexico)| Having migrated internally by 2003 compared to those started receiving programme two years later (Boys 9-15 in 1997) | 0.02 | Percent point change | 10% | | | | Oportunidades (Mexico)| Having migrated internally by 2003 compared to those started receiving programme two years later (Girls 9-10 in 1997) | -0.035 | Percent point change | 10% | | | | Oportunidades (Mexico)| Having migrated internally by 2003 compared to those started receiving programme two years later (Girls 11-12 in 1998) | 0.021 | Percent point change | NS |

Notes: results represent all overall results reported and do not include those disaggregated by gender or showing the effect of variations in design features. Figures in bold indicate statistically significant. NS means the study did not find a statistically significant result, typically up to the 10% significance level.

### Table A5.5.10 Effect of design and implementation features on adult employment outcomes

| # | Study | Programme and country | Effect of [design / implementation feature] | Outcome variable and treatment population | Effect | Measure of change | Significance | |---|-------|------------------------|---------------------------------------------|-------------------------------------------|--------|-------------------|-------------| | **Official recipient** | | | | | | | | | 1 | Siaplay (2012) | SA-OAP (South Africa) | Official recipient (only female household member is receiving OAP) | Whether employed or not (female 21-26) | 0.103 | Percentage points | NS | | | | | | | -0.124 | Percentage points | NS | | | | | | | -0.187 | Percentage points | 5% | | | | | | | 0.143 | Percentage points | 5% | | **Transfer timing** | | | | | | | | | 1 | Bazzi et al. (2012) | Temporary UCT (Indonesia) | No. of hours worked per week per adult – 2006 follow up (after one disbursement) | | -1.838 | Hours per week | 5% | | | | | | | -0.427 | Hours per week | NS | | | | | | | -2.285 | Hours per week | 5% | | | | | | | -0.173 | Hours per week | NS | | **Conditionalities** | | | | | | | | | 1 | Angelucci (2004) | PROGRESA (Mexico) | Behavioural requirement (households with at least one secondary school eligible male (i.e. part of grant conditional on attendance) vs. where all transfers unconditional) | Migration to US 1998 (household level) | 0.0025 | Percentage points | NS | | | | | | | -0.0086 | Percentage points | 1% | | | | | | | 0.0174 | Percentage points | NS | | | | | | | 0.0155 | Percentage points | NS | | | | | | | 0.0205 | Percentage points | NS | | | | | | | -0.0015 | Percentage points | NS | | **Duration of exposure** | | | | | | | | | 1 | Bazzi et al. (2012) | Temporary UCT (Indonesia) | Duration – 2006 follow-up and after 1 disbursement | Hours worked per week per adult | -1.838 | Hours per week | 5% | | | | | | | -2.285 | Hours per week | 5% | | | | | | | -0.427 | Hours per week | NS | | | | | | | -0.173 | Hours per week | NS |

*continued on next page* Table A5.5.10 Effect of design and implementation features on adult employment outcomes

| # | Study | Programme and country | Effect of design / implementation feature | Outcome variable and treatment population | Effect | Measure of change | Significance | |----|--------------------------------------------|-----------------------|-------------------------------------------|----------------------------------------------------------------------------------------------------------|--------|------------------|--------------| | 2 | Behrman and Parker (2013) | PROGRESA/ Oportunidades (Mexico) | Additional 1.5 years exposure to programme | Proportion working in the previous week in activity contributing to family income (Women aged 50 or older) | 0.05 | Percentage point | 10% | | | | PROGRESA/ Oportunidades (Mexico) | Additional 1.5 years exposure to programme | Proportion working in the previous week in activity contributing to family income (Men aged 50 or older) | -0.034 | Percentage point | NS | | 3 | Buser et al. (2014) | BDH (Ecuador) | Duration of exposure (long-term transfer recipients vs. those that lost them around 2 years ago) | Number of hours worked (mothers) | 8.42 | ‘Hours’ | 10% | | 4 | Maluccio (2005) | RPS (Nicaragua) | Duration of exposure (1 year after baseline) | Total hours worked last week by household members | -3.9191| Hours per week | NS | | | | RPS (Nicaragua) | Duration of exposure (2 years after baseline) | Total hours worked last week by household members | 0.3406 | Hours per week | NS | | | | RPS (Nicaragua) | Duration of exposure (1 year after baseline) | Average hours per worker worked last week | -0.4825| Hours per week | NS | | | | RPS (Nicaragua) | Duration of exposure (2 years after baseline) | Average hours per worker worked last week | 0.7732 | Hours per week | NS |

**Transfer level**

| # | Study | Programme and country | Effect of design / implementation feature | Outcome variable and treatment population | Effect | Measure of change | Significance | |----|--------------------------------------------|-----------------------|-------------------------------------------|----------------------------------------------------------------------------------------------------------|--------|------------------|--------------| | 1 | Bertrand et al. (2003) | SA-OAP (South Africa) | Level of transfer (effect of 1000 rand change in individual income) | Individual is working (prime aged adults living with eligible elderly) | -0.099 | Percent point | 5% | | | | SA-OAP (South Africa) | Level of transfer (effect of 1000 rand change in individual income) | Employed (female 16-50 year olds who live with age-eligible elderly) | -0.023 | Percentage point | NS | | | | SA-OAP (South Africa) | Level of transfer (effect of 1000 rand change in individual income) | Employed (male 16-50 year olds who live with age-eligible elderly) | -0.201 | Percentage point | 5% | | | | SA-OAP (South Africa) | Level of transfer (effect of 1000 rand change in individual income) | No. of hours worked (16-50 year olds who live with age-eligible elderly) | -17.07 | Hours per week | 5% | | | | SA-OAP (South Africa) | Level of transfer (effect of 1000 rand change in individual income) | No. of hours worked (female 16-50 year olds who live with age-eligible elderly) | -13.27 | Hours per week | 5% | | | | SA-OAP (South Africa) | Level of transfer (effect of 1000 rand change in individual income) | No. of hours worked (male 16-50 year olds who live with age-eligible elderly) | -22.48 | Hours per week | 5% | | 2 | Angelucci (2004) | PROGRESA (Mexico) | Transfer level (receiving high grant vs. low grant) | US migration 1998 (household level) | 0.012 | Percentage point | 5% | | | | PROGRESA (Mexico) | Transfer level (receiving high grant vs. low grant) | US migration 1999 (household level) | 0.0243 | Percentage point | 1% | | | | PROGRESA (Mexico) | Transfer level (receiving high grant vs. low grant) | Mexican migration 1998 (household level) | -0.0088| Percentage point | 5% | | | | PROGRESA (Mexico) | Transfer level (receiving high grant vs. low grant) | Mexican migration 1999 (household level) | -0.0096| Percentage point | 10% | | | | PROGRESA (Mexico) | Transfer level (receiving high grant vs. low grant) | All migration 1998 (household level) | -0.0009| Percentage point | NS | | | | PROGRESA (Mexico) | Transfer level (receiving high grant vs. low grant) | All migration 1999 (household level) | .0030 | Percentage point | NS | | 3 | Bazzi et al. (2012) | Temporary UCT (Indonesia) | Transfer level (transfers per capita in 000,000s Rupiah) | Change in weekly hours worked per adult, between 2005 and 2006 | -0.391 | Hours per week | NS | | | | Temporary UCT (Indonesia) | Transfer level (transfers per capita in 000,000s Rupiah) | Change in weekly hours worked per adult, between 2005 and 2007 (Total hours / no. of adult members) | -0.256 | Hours per week | NS |

continued on next page Table A5.5.10 Effect of design and implementation features on adult employment outcomes

| # | Study | Programme and country | Effect of [design / implementation feature] | Outcome variable and treatment population | Effect Measure of change | Significance | |----|--------------------------------------------|-----------------------|---------------------------------------------|-------------------------------------------|--------------------------|--------------| | 4 | Dabalen et al. (2008) | NE (Albania) | Transfer level (transfers per household in 100s of Lek) | Hours worked last week (all adults) | -0.0667 | Hours per week 5% | | | | | | Hours worked last week (females adults) | -0.0783 | Hours per week 5% | | | | | | Hours worked last week (male adults) | -0.0163 | Hours per week NS | | | | | | Decision to work (all adults) | -0.0021 | Percentage point 1% | | | | | | Decision to work (females adults) | -0.0023 | Percentage point NS | | | | | | Decision to work (male adults) | 0.0016 | Percentage point 1% | | | | | | Whether working or not (Male) | -0.0016 | Fixed effects coefficient NS | | | | | | Whether working or not (Female) | -0.0023 | Fixed effects coefficient 1% |

**Targeting**

| # | Study | Programme and country | Effect of [design / implementation feature] | Outcome variable and treatment population | Effect Measure of change | Significance | |----|--------------------------------------------|-----------------------|---------------------------------------------|-------------------------------------------|--------------------------|--------------| | 1 | Merttens et al. (2015) | SAGE (Uganda) | Among households targeted through the Senior Citizens Grant | Proportion of working-age adults (18-64) engaged in any economically productive activities | 0.0062 | Percentage point NS | | | | | | Proportion of working-age adults (18-64) engaged in any economically productive activities | -0.012 | Percentage point NS | | | | | | Mean number of hours spent working per week (all occupations) | -0.02 | Hours NS | | | | | | Mean number of hours spent working per week (all occupations) | 0.48 | Hours NS | | | | | | Mean number of months spent working in main occupation in last year | 0.16 | Months NS | | | | | | Mean number of months spent working in main occupation in last year | 0.45 | Months 10% | | | | | | Proportion of individuals engaged in casual labour as main or secondary activity | -0.0002 | Percentage point NS | | | | | | Proportion of individuals engaged in casual labour as main or secondary activity | -0.0002 | Percentage point NS |

**Complementary interventions and supply side services**

| # | Study | Programme and country | Effect of [design / implementation feature] | Outcome variable and treatment population | Effect Measure of change | Significance | |----|--------------------------------------------|-----------------------|---------------------------------------------|-------------------------------------------|--------------------------|--------------| | 1 | Blattman et al. (2015) | WINGS (Uganda) | Difference between those receiving no group training and those receiving group training (organisational development, decision-making, leadership and savings and credit group formation) | Involved in any non-farm self-employment (16 m after grants) | 0.008 | Percentage point NS | | | | | | Started enterprise since baseline (16m after grant) | -0.002 | Percentage point NS | | | | | | Average work hours per week (16m after grant) | 0.486 | Percentage point NS | | | | | | Average agricultural hours per week (16m after grant) | 0.506 | Hours NS |

continued on next page

### Table A5.5.10 Effect of design and implementation features on adult employment outcomes continued

| # | Study | Programme and country | Effect of [design / implementation feature] | Outcome variable and treatment population | Effect Measure of change | Significance | |----|-------|-----------------------|---------------------------------------------|-------------------------------------------|-------------------------|-------------| | 1 | WINGS (Uganda) | Difference between those receiving no group training and those receiving group training | Average non-agricultural hours per week (16m after grant) | -0.020 Hours | NS | | | WINGS (Uganda) | Difference between those getting 2 supervisory visits (no advice) and those getting 5 (extended advice) | Any non-farm self-employment (12m after grants) | 0.042 Percentage point | NS | | | WINGS (Uganda) | Difference between those getting 2 supervisory visits (no advice) and those getting 5 (extended advice) | Started enterprise since baseline (12m after grant) | 0.016 Percentage point | NS | | | WINGS (Uganda) | Difference between those getting 2 supervisory visits (no advice) and those getting 5 (extended advice) | Average work hours per week (12m after grant) | 3.659 Percentage point | NS | | | WINGS (Uganda) | Difference between those getting 2 supervisory visits (no advice) and those getting 5 (extended advice) | Agricultural work hours per week (12m after grant) | 2.757 Hours | NS | | | WINGS (Uganda) | Difference between those getting 2 supervisory visits (no advice) and those getting 5 (extended advice) | Non-agricultural work hours per week (12m after grant) | 0.902 Hours | NS | | 2 | Green et al. (2015) | WINGS (Uganda) | Women who were joined as beneficiaries by their partner (or someone from their household who makes financial decisions), and received basic training in couples’ communication and problem solving (relative to regular beneficiaries who participated alone). | Average (non-agricultural) work hours per week among women | -1.23 Hours per week | NS | | 3 | Macours and Vakis (2012) | Atención a Crisis (Nicaragua) | Basic CCT | Non-agricultural wage employment | 0.0221 Percent point change | NS | | | Atención a Crisis (Nicaragua) | Basic CCT plus a scholarship for a vocational training | Non-agricultural wage employment | 0.0177 Percent point change | NS | | | Atención a Crisis (Nicaragua) | Basic CCT plus a productive investment grant | Non-agricultural wage employment | -0.0211 Percent point change | NS | | | Atención a Crisis (Nicaragua) | Basic CCT | Non-agricultural self-employment | 0.0396 Percent point change | 10% | | | Atención a Crisis (Nicaragua) | Basic CCT plus a scholarship for a vocational training | Non-agricultural self-employment | 0.0383 Percent point change | 10% | | | Atención a Crisis (Nicaragua) | Basic CCT plus a productive investment grant | Non-agricultural self-employment | 0.126 Percent point change | 1% |

### Table A5.5.11 Effect of design and implementation features on child labour outcomes

| # | Study | Programme and country | Effect of [design / implementation feature] | Outcome variable and treatment population | Effect Measure of change | Significance | |----|------------------------|-----------------------|---------------------------------------------|-------------------------------------------|--------------------------|--------------| | | **Official recipient** | | | | | | | 1 | Siaplay (2012) | SA-OAP (South Africa) | Official recipient (only female household member is receiving OAP) | Whether employed or not (female 14-20) | -0.018 Percentage points | NS | | | | | Official recipient (only male household member is receiving OAP) | Whether employed or not (female 14-20) | -0.003 Percentage points | NS | | | | | Official recipient (only female household member is receiving OAP) | Whether employed or not (male 14-20) | 0.023 Percentage points | NS | | | | | Official recipient (only male household member is receiving OAP) | Whether employed or not (male 14-20) | -0.065 Percentage points | NS | | | **Conditionalities** | | | | | | | 1 | Barrera-Osorio et al. (2011) | SCAE (Colombia) | Behavioural requirement (basic transfer conditional on school attendance) | primary activity is work (children grade 6-10) | -0.002 Percent point change | NS | | | | | Behavioural requirement (savings treatment that postpones a bulk of the transfer due to good attendance to just before children have to re-enrol) | primary activity is work (children grade 6-10) | -0.001 Percent point change | NS | | | | | Behavioural requirement (some of the transfer is conditional on students' graduation and tertiary enrolment rather than attendance) | primary activity is work (children grade 6-10) | -0.008 Percent point change | 10% | | | | | Behavioural requirement (basic transfer conditional on school attendance) | Hours worked last week (children grade 6-10) | -0.371 Hours per week | 5% | | | | | Behavioural requirement (savings treatment that postpones a bulk of the cash transfer due to good attendance to just before children have to re-enrol) | Hours worked last week (children grade 6-10) | -0.248 Hours per week | 10% | | | | | Behavioural requirement (some of the transfer is conditional on students' graduation and tertiary enrolment rather than attendance) | Hours worked last week (children grade 6-10) | -0.804 Hours per week | 5% | | | | | Behavioural requirement (basic transfer conditional on school attendance) | primary activity is work (children grade 11) | -0.004 Percent point change | NS | | | | | Behavioural requirement (savings treatment that postpones a bulk of the cash transfer due to good attendance to just before children have to re-enrol) | primary activity is work (children grade 11) | 0.031 Percent point change | NS | | | | | Behavioural requirement (some of the transfer is conditional on students' graduation and tertiary enrolment rather than attendance) | primary activity is work (children grade 11) | -0.153 Percent point change | 1% | | | | | Behavioural requirement (basic conditional cash transfer treatment based on school attendance) | Hours worked last week (children grade 11) | 0.683 Hours per week | NS | | | | | Behavioural requirement (savings treatment that postpones a bulk of the cash transfer due to good attendance to just before children have to re-enrol) | Hours worked last week (children grade 11) | 0.092 Level change | NS | | | | | Behavioural requirement (some of the transfer is conditional on students' graduation and tertiary enrolment rather than attendance) | Hours worked last week (children grade 11) | -7.349 Hours per week | 1% |

*continued on next page* Table A5.5.11 Effect of design and implementation features on child labour outcomes

| # | Study | Programme and country | Effect of [design / implementation feature] | Outcome variable and treatment population | Effect | Measure of change | Significance | |----|--------------------------------------------|-----------------------|-------------------------------------------------------------------------------------------------------------|-------------------------------------------|--------|-------------------|--------------| | 2 | Schady and Araujo (2006) | BDH (Ecuador) | Behavioural monitoring (Household perception that continued receipt of transfer conditional on school enrolment) | Child is working in follow-up survey | -0.081 | Percentage points | NS | | | | | Behavioural monitoring (Household perception that transfers are not conditional on any behaviour) | Child is working in follow-up survey | -0.055 | Percentage points | NS | | | | | Behavioural monitoring (Household perception that continued receipt of transfer conditional on school enrolment) | Child is working full-time (40+ hours) | -0.078 | Percentage points | 5% | | | | | Behavioural monitoring (Household perception that transfers are not conditional on any behaviour) | Child is working full-time (40+ hours) | 0.009 | Percentage points | NS | | | | | Behavioural monitoring (Households perceiving there to be a condition of school enrolment for continuing to receive transfers) | Hours worked in past week | -5.92 | Hours worked | 1% | | | | | Behavioural monitoring (Households perceiving there to be no conditions attached to the transfers) | Hours worked in past week | -0.024 | Hours worked | NS | | 3 | Benedetti et al. (2015) | Bono 10,000 (Honduras) | Treatment household with just one eligible child (school enrolment conditions only apply to one child) | Worked for more than one hour | -0.062 | Percentage point | 5% | | | | | Treatment households with more than one eligible child (school enrolment conditions only apply to one child) | Worked for more than one hour | Various | Percentage point | No results significant |

Duration of exposure

| # | Study | Programme and country | Duration of exposure (benefitting from transfers for approx. 5.5 years versus 4) | Whether working in 2003 (boys 9-15 in 1997) | -4.1 | Percent | 10% | |----|--------------------------------------------|-----------------------|--------------------------------------------------------------------------------|---------------------------------------------|--------|-------------------|--------------| | | | | Duration of exposure (benefitting from transfers for approx. 5.5 years versus 4) | Whether working in 2003 (girls 9-15 in 1997) | -5 | Percent | NS | | 2 | Perova and Vakis (2012) | Juntos (Peru) | Duration of exposure (12 to 23 months in Juntos) | Worked in previous week (6-14 year olds) | 0 | Percentage points | NS | | | | | Duration of exposure (24 to 36 months in Juntos) | Worked in previous week (6-14 year olds) | 0.03 | Percentage points | 10% | | | | | Duration of exposure (Over 36 months in Juntos) | Worked in previous week (6-14 year olds) | 0.13 | Percentage points | 1% | | 3 | Behrman et al. (2009) | PROGRESA/Oportunidades (Mexico) | Duration of exposure (beneficiary households that started receiving transfers in 1998 vs. 2000) | Whether working in 2003 (girls 9-15 in 1997) | -0.013 | Percent point change | NS | | | | | Duration of exposure (beneficiary households that started receiving transfers in 1998 vs. 2000) | Whether working in 2003 (boys 9-15 in 1997) | -0.027 | Percent point change | 10% | | | | | Duration of exposure (beneficiary households that started receiving transfers in 1998 vs. 2000) | Whether working in 2003 (Girls 9-15 in 1997) | -0.008 | Percent point change | NS | | | | | Duration of exposure (beneficiary households that started receiving transfers in 1998 vs. 2000) | Whether working in 2003 (Girls 11-12 in 1998) | -0.01 | Percent point change | NS | | | | | Duration of exposure (beneficiary households that started receiving transfers in 1998 vs. 2000) | Whether working in 2003 (Girls 13-15 in 1998) | 0.02 | Percent point change | NS | | | | | Duration of exposure (beneficiary households that started receiving transfers in 1998 vs. 2000) | Proportion of girls 9-15 in 1997 having migrated by 2003 | -0.09 | Percent point change | NS |

continued on next page Table A5.5.11 Effect of design and implementation features on child labour outcomes

| # | Study | Programme and country | Effect of [design / implementation feature] | Outcome variable and treatment population | Effect | Measure of change | Significance | |----|------------------------|----------------------------------------|---------------------------------------------|-------------------------------------------|--------|-------------------|--------------| | 3 | Behrman et al. (2009) | PROGRESA/ Oportunidades (Mexico) | Duration of exposure (beneficiary households that started receiving transfers in 1998 vs. 2000) | Proportion of boys 9-15 in 1997 having migrated by 2003 | 0.02 | Percent point change | 10% | | | | | | Proportion of girls 9-10 in 1997 having migrated by 2003 | -0.035 | Percent point change | 10% | | | | | | Proportion of girls 11-12 in 1998 having migrated by 2003 | 0.021 | Percent point change | NS | | | | | | Proportion of girls 13-15 in 1999 having migrated by 2003 | 0.014 | Percent point change | NS | | 4 | Berhman et al. (2012) | Oportunidades (Mexico) | Duration of exposure (after 1 year) | Employed for pay (urban boys 12-14 years old) | -0.077 | Percentage point | 5% | | | | | | Employed for pay (urban boys 12-14 years old) | -0.124 | Percentage point | 5% | | | | | | Employed for pay (urban boys 15-18 years old) | 0.028 | Percentage point | NS | | | | | | Employed for pay (urban boys 15-18 years old) | -0.051 | Percentage point | NS | | | | | | Employed for pay (urban boys 19-20 years old) | -0.059 | Percentage point | NS | | | | | | Employed for pay (urban boys 19-20 years old) | -0.154 | Percentage point | NS | | | | | | Employed for pay (urban boys 6-20 years old) | -0.041 | Percentage point | NS | | | | | | Employed for pay (urban boys 6-20 years old) | -0.103 | Percentage point | 5% | | | | | | Employed for pay (urban girls 12-14 years old) | 0.007 | Percentage point | NS | | | | | | Employed for pay (urban girls 12-14 years old) | -0.01 | Percentage point | NS | | | | | | Employed for pay (urban girls 15-18 years old) | -0.0105 | Percentage point | 10% | | | | | | Employed for pay (urban girls 15-18 years old) | 0.004 | Percentage point | NS | | | | | | Employed for pay (urban girls 19-20 years old) | -0.05 | Percentage point | NS | | | | | | Employed for pay (urban girls 19-20 years old) | 0.087 | Percentage point | NS | | | | | | Employed for pay (urban girls 6-20 years old) | -0.038 | Percentage point | NS | | | | | | Employed for pay (urban girls 6-20 years old) | 0.002 | Percentage point | NS | | 5 | Dammert (2008) | RPS (Nicaragua) | Duration of exposure (2001) | Participation in labour activities (boys 7-13 years old at baseline) | -0.099 | Percentage point | 5% | | | | | | Participation in labour activities (boys 7-13 years old at baseline) | -0.124 | Percentage point | 5% | | | | | | Participation in labour activities (girls 7-13 years old at baseline) | -0.012 | Percentage point | NS | | | | | | Participation in labour activities (girls 7-13 years old at baseline) | -0.014 | Percentage point | NS | | | | | | Participation in labour activities (children 7-13 years old at baseline – male headed) | -0.076 | Percentage points | 10% |

continued on next page Table A5.5.11 Effect of design and implementation features on child labour outcomes continued

| # | Study | Programme and country | Effect of [design / implementation feature] | Outcome variable and treatment population | Effect | Measure of change | Significance | |----|------------------------|-----------------------|---------------------------------------------|-------------------------------------------|--------|------------------|--------------| | 5 | Dammert (2008) | RPS (Nicaragua) | Duration of exposure (2002) | Participation in labour activities (children 7-13 years old at baseline – male headed) | -0.05 | Percentage points | NS | | | | | | Participation in labour activities (children 7-13 years old at baseline – female headed) | -0.131 | Percentage points | 5% | | | | | | Participation in labour activities (children 7-13 years old at baseline – female headed) | -0.082 | Percentage points | NS | | 6 | Maluccio (2005) | RPS (Nicaragua) | Duration of exposure (1 year after baseline) | Working (girls 7-12 years) | -0.0077| Percentage point | NS | | | | | | Working (girls 7-12 years) | 0.0553 | Percentage point | 10% | | | | | | Working (boys 7-12 years) | -0.0415| Percentage point | NS | | | | | | Working (boys 7-12 years) | -0.0175| Percentage point | NS |

Targeting

1. Merttens et al. (2015) SAGE (Uganda) Among households targeted through the Senior Citizens Grant Proportion of children aged 6-17 engaged in child labour -0.0004 Percentage point NS

SAGE (Uganda) Among households targeted through the Vulnerable Family Support Grant Proportion of children aged 6-17 engaged in child labour 0.0001 Percentage point NS

Complementary interventions and supply-side services

1. Del Carpio (2008) Atención a Crisis (Nicaragua) Complementary interventions (basic intervention) Physical labour (ages 8-15) -1.052 Hours per week NS

Atención a Crisis (Nicaragua) Complementary interventions (training intervention) Physical labour (ages 8-15) -1.407 Hours per week 5%

Atención a Crisis (Nicaragua) Complementary interventions (business grant intervention) Physical labour (ages 8-15) -1.013 Hours per week NS

Atención a Crisis (Nicaragua) Complementary interventions (basic intervention) Non-physical labour (ages 8-15) 1.414 Hours per week NS

Atención a Crisis (Nicaragua) Complementary interventions (training intervention) Non-physical labour (ages 8-15) 1.155 Hours per week NS

Atención a Crisis (Nicaragua) Complementary interventions (business grant intervention) Non-physical labour (ages 8-15) 6.288 Hours per week 1%

Atención a Crisis (Nicaragua) Complementary interventions (basic intervention) No. of hours worked (ages 8-15) -1.143 Hours per week NS

Atención a Crisis (Nicaragua) Complementary interventions (training intervention) No. of hours worked (ages 8-15) -1.62 Hours per week 5%

Atención a Crisis (Nicaragua) Complementary interventions (business grant intervention) No. of hours worked (ages 8-15) -0.533 Hours per week NS

Atención a Crisis (Nicaragua) Complementary interventions (basic intervention) No. of hours worked (girls ages 8-15) -0.551 Hours per week NS

Atención a Crisis (Nicaragua) Complementary interventions (training intervention) No. of hours worked (girls ages 8-15) -1.126 Hours per week NS

Atención a Crisis (Nicaragua) Complementary interventions (business grant intervention) No. of hours worked (girls ages 8-15) -0.076 Hours per week NS

Atención a Crisis (Nicaragua) Complementary interventions (basic intervention) No. of hours worked (boys ages 8-15) -1.675 Hours per week 10%

Atención a Crisis (Nicaragua) Complementary interventions (training intervention) No. of hours worked (boys ages 8-15) -2.073 Hours per week 5%

Atención a Crisis (Nicaragua) Complementary interventions (business grant intervention) No. of hours worked (boys ages 8-15) -0.989 Hours per week NS

14 Definition of work excludes domestic work, which may underestimate impacts for girls, though Skoufias and Parker (2001) find evidence that in initial years the programme reduced time spent in domestic work for girls.

## Summary results for Empowerment

### Table A5.6.1 Summary of results for the role of cash transfer design and implementation parameters on empowerment

| Paper | Specific variable | Size of effect | Unit of change | Statistical significance | Gender of individual | Disaggregation | Programme | |-------|------------------|----------------|----------------|--------------------------|----------------------|----------------|-----------| | **Main recipient** | | | | | | | | | 1 Siaplay (2012) | Married at time of survey | -0.07 | Percentage points | NS | Female | Transfer (pension) recipient is female | SA-OAP (South Africa) | | | Married at time of survey | 0.227 | Percentage points | 1% | Female | Transfer (pension) recipient is male | SA-OAP (South Africa) | | | Married at time of survey | -0.269 | Percentage points | 1% | Male | Transfer (pension) recipient is female | SA-OAP (South Africa) | | | Married at time of survey | 0.243 | Percentage points | 1% | Male | Transfer (pension) recipient is male | SA-OAP (South Africa) | | **Transfer level** | | | | | | | | | 1 Angelucci (2008) | Male partner is aggressive when drinking | -0.016 | Percentage points | 1% | Female | | PROGRESA (Mexico) | | | Male partner is aggressive when drinking | 0.051 | Percentage points | 5% | Female | Transfer level (maximum transfer) | PROGRESA (Mexico) | | 2 Kohler and Thornton (2012) | Condom use (in last nine days) | 0.041 | Percentage points | NS | Male | High transfer | M-IP (Malawi) | | | Condom use (in last nine days) | 0.063 | Percentage points | NS | Male | Low transfer | M-IP (Malawi) | | | Safe sex (used a condom at last sex or did not have sex in last nine days) | -0.092 | Percentage points | 5% | Male | High transfer | M-IP (Malawi) | | | Safe sex (used a condom at last sex or did not have sex in last nine days) | -0.088 | Percentage points | 5% | Male | Low transfer | M-IP (Malawi) | | | Condom use (in last nine days) | -0.019 | Percentage points | NS | Female | High transfer | M-IP (Malawi) | | | Condom use (in last nine days) | 0.02 | Percentage points | NS | Female | Low transfer | M-IP (Malawi) | | | Safe sex (used a condom at last sex or did not have sex in last nine days) | 0.087 | Percentage points | 10% | Female | High transfer | M-IP (Malawi) | | | Safe sex (used a condom at last sex or did not have sex in last nine days) | 0.046 | Percentage points | NS | Female | Low transfer | M-IP (Malawi) | | **Duration of exposure** | | | | | | | | | 1 Baird et al. (2011) | Ever pregnant | -0.009 | Percentage points | NS | Female | 12 months, UCT | ZCTP (Malawi) | | | Ever pregnant | -0.067 | Percentage points | 1% | Female | 24 months, UCT | ZCTP (Malawi) | | | Ever pregnant | 0.013 | Percentage points | NS | Female | 12 months, CCT | ZCTP (Malawi) | | | Ever pregnant | 0.029 | Percentage points | NS | Female | 24 months, CCT | ZCTP (Malawi) | | | Ever married | -0.026 | Percentage points | 5% | Female | 12 months, UCT | ZCTP (Malawi) | | | Ever married | -0.079 | Percentage points | 1% | Female | 24 months, UCT | ZCTP (Malawi) | | | Ever married | 0.007 | Percentage points | NS | Female | 12 months, CCT | ZCTP (Malawi) | | | Ever married | -0.012 | Percentage points | NS | Female | 24 months, CCT | ZCTP (Malawi) |

*continued on next page* Table A5.6.1 Summary of results for the role of cash transfer design and implementation parameters on empowerment continued

| Paper | Specific variable | Size of effect | Unit of change | Statistical significance | Gender of individual | Disaggregation | Programme | |-------|------------------|----------------|----------------|--------------------------|----------------------|----------------|-----------| | 2 | Married at time of survey | -0.01 | Percentage points | NS | Female | PROGRESA (Mexico) | | | Married at time of survey | -0.006 | Percentage points | NS | Male | PROGRESA (Mexico) | | | Married at time of survey | -0.007 | Percentage points | NS | Female | Aged 9-10 in 1997 | PROGRESA (Mexico) | | | Married at time of survey | -0.008 | Percentage points | NS | Female | Aged 11-12 in 1997 | PROGRESA (Mexico) | | | Married at time of survey | -0.019 | Percentage points | NS | Female | Aged 13-15 in 1997 | PROGRESA (Mexico) | | | Married at time of survey | 0.008 | Percentage points | NS | Male | Aged 9-10 in 1997 | PROGRESA (Mexico) | | | Married at time of survey | -0.014 | Percentage points | NS | Male | Aged 11-12 in 1997 | PROGRESA (Mexico) | | | Married at time of survey | -0.013 | Percentage points | NS | Male | Aged 13-15 in 1997 | PROGRESA (Mexico) | | 3 | Use of contraceptives | 0.08 | Percentage points | 1% | Female | 12-23 months | Juntos (Peru) | | | Use of contraceptives | 0.12 | Percentage points | 1% | Female | 24 to 36 months | Juntos (Peru) | | | Use of contraceptives | 0.18 | Percentage points | 1% | Female | Over 36 months | Juntos (Peru) |

Conditionalities

| Paper | Specific variable | Size of effect | Unit of change | Statistical significance | Gender of individual | Disaggregation | Programme | |-------|------------------|----------------|----------------|--------------------------|----------------------|----------------|-----------| | 1 | Ever married | 0.007 | Percentage points | NS | Female | CCT treatment arm | ZCTP (Malawi) | | | Ever married | -0.026 | Percentage points | 5% | Female | UCT treatment arm | ZCTP (Malawi) | | | Ever married | 0.037 | Percentage points | NS | Female | Aged over 15, CCT treatment arm | ZCTP (Malawi) | | | Ever married | 0.007 | Percentage points | NS | Female | Aged over 15, UCT treatment arm | ZCTP (Malawi) | | | Ever pregnant | 0.013 | Percentage points | NS | Female | CCT treatment arm | ZCTP (Malawi) | | | Ever pregnant | -0.009 | Percentage points | NS | Female | UCT treatment arm | ZCTP (Malawi) | | | Ever pregnant | 0.104 | Percentage points | 5% | Female | Aged over 15, CCT treatment arm | ZCTP (Malawi) | | | Ever pregnant | -0.032 | Percentage points | NS | Female | Aged over 15, UCT treatment arm | ZCTP (Malawi) | | 2 | Ever married | 0.93 | Odds ratio | NS | Female | CCT treatment arm | ZCTP (Malawi) | | | Ever married | 0.36 | Odds ratio | NS | Female | UCT treatment arm | ZCTP (Malawi) |

Payment mechanism

| Paper | Specific variable | Size of effect | Unit of change | Statistical significance | Gender of individual | Disaggregation | Programme | |-------|------------------|----------------|----------------|--------------------------|----------------------|----------------|-----------| | 1 | Female recipient responsible for spending part of cash transfer | -0.01 | Percentage points | NS | Female | Zap (mobile payment) treatment arm | Mobile money experiment (Niger) | | | Female recipient responsible for spending part of cash transfer | 0.02 | Percentage points | NS | Female | Cash treatment arm that also received mobile phone | Mobile money experiment (Niger) | | | Female recipient responsible for spending part of cash transfer | 0.01 | Percentage points | NS | Female | Zap (mobile payment) treatment arm | Mobile money experiment (Niger) | | | Female recipient involved in deciding how transfer is spent | 0.01 | Percentage points | NS | Female | Zap (mobile payment) treatment arm | Mobile money experiment (Niger) |

continued on next page

### Table A5.6.1 Summary of results for the role of cash transfer design and implementation parameters on empowerment continued

| Paper | Specific variable | Size of effect | Unit of change | Statistical significance | Gender of individual | Disaggregation | Programme | |-------|------------------|----------------|----------------|--------------------------|----------------------|----------------|-----------| | 1 | Aker et al. (2014) | Female recipient involved in deciding how transfer is spent | 0.01 | Percentage points | NS | Female | Cash treatment arm that also received mobile phone | Mobile money experiment (Niger) | | | | Female recipient involved in deciding how transfer is spent | 0.00 | Percentage points | NS | Female | Zap (mobile payment) treatment arm | Mobile money experiment (Niger) | | 2 | Aker et al. (2011) | Respondent involved in deciding how transfer is spent (not entirely clear that respondent is female recipient) | 0.00 | Percentage points | NS | Female | Zap (mobile payment) treatment arm | Mobile money experiment (Niger) | | | | Respondent involved in deciding how transfer is spent | 0.01 | Percentage points | 10% | Female | Cash treatment arm that also received mobile phone | Mobile money experiment (Niger) | | | | Respondent involved in deciding how transfer is spent | 0.01 | Percentage points | 10% | Female | Cash treatment arm | Mobile money experiment (Niger) | | | | Respondent involved in deciding how transfer is spent | 0.00 | Percentage points | NS | Female | Zap (mobile payment) treatment arm | Mobile money experiment (Niger) | | | | Respondent involved in deciding how transfer is spent | 0.01 | Percentage points | NS | Female | Zap (mobile payment) treatment arm | Mobile money experiment (Niger) | | | | Respondent involved in deciding how transfer is spent | 0.08 | Percentage points | NS | Female | Zap (mobile payment) treatment arm – Fulani and Touareg ethnic groups only | Mobile money experiment (Niger) | | | | Respondent involved in deciding how transfer is spent | 0.01 | Percentage points | NS | Female | Zap (mobile payment) treatment arm – Hausa ethnic group only | Mobile money experiment (Niger) |

**Complementary interventions and supply-side services**

| Paper | Specific variable | Size of effect | Unit of change | Statistical significance | Gender of individual | Disaggregation | Programme | |-------|------------------|----------------|----------------|--------------------------|----------------------|----------------|-----------| | 1 | Blattman et al. (2015) | Physical and emotional abuse (z-score) | 0.066 | Z-score | NS | Female | WINGS (Uganda) | | | | Physical and emotional abuse (z-score) | -0.046 | Z-score | NS | Female | Complementary programmes | WINGS (Uganda) | | | | Autonomy in purchases (z-score) | 0.082 | Z-score | NS | Female | WINGS (Uganda) | | | | Autonomy in purchases (z-score) | 0.089 | Z-score | NS | Female | WINGS (Uganda) | | | | Degree of partner control | 0.17 | Percentage points | NS | Female | WINGS (Uganda) | | | | Degree of partner control | 0.129 | Percentage points | 10% | Female | WINGS (Uganda) | | 2 | Green et al. (2015) | Self-reported autonomy/influence in purchase (z-score) | -0.11 | Z-score | 10% | Female | All female WINGS+ beneficiaries | WINGS (Uganda) | | | | Self-reported autonomy/influence in purchase (z-score) | -0.07 | Z-score | NS | Female | Beneficiaries who had an intimate partner at baseline | WINGS (Uganda) | | | | Physical and emotional abuse | 0.01 | Percentage points | NS | Female | All female WINGS+ beneficiaries | WINGS (Uganda) | | | | Physical and emotional abuse | -0.08 | Percentage points | NS | Female | Beneficiaries who had an intimate partner at baseline | WINGS (Uganda) | | | | Controlling behaviour | -0.01 | Percentage points | NS | Female | All female WINGS+ beneficiaries | WINGS (Uganda) | | | | Controlling behaviour | -0.07 | Percentage points | NS | Female | Beneficiaries who had an intimate partner at baseline | WINGS (Uganda) |

*continued on next page*

### Table A5.6.1 Summary of results for the role of cash transfer design and implementation parameters on empowerment continued

| Paper | Specific variable | Size of effect | Unit of change | Statistical significance | Gender of individual | Disaggregation | Programme | |-------|------------------|----------------|----------------|--------------------------|----------------------|----------------|-----------| | 1 | Merttens et al. (2015) | Female is decision maker on what to do about a serious health problem | 0.032 | Percentage points | NS | Female | SCG | SAGE (Uganda) | | | | Female is decision maker on what to do about a serious health problem | -0.0095 | Percentage points | NS | Female | SCG | SAGE (Uganda) | | | | Female is decision maker on children’s education | 0.042 | Percentage points | NS | Female | VFSG | SAGE (Uganda) | | | | Female is decision maker on children’s education | -0.002 | Percentage points | NS | Female | VFSG | SAGE (Uganda) | | | | Female is decision maker on how to invest money | 0.0081 | Percentage points | NS | Female | SCG | SAGE (Uganda) | | | | Female is decision maker on how to invest money | -0.0056 | Percentage points | NS | Female | VFSG | SAGE (Uganda) |

Notes: *In Behrman et al. (2005) the treatment group were exposed to treatment for 1.5 years longer (4.5 years as opposed to 3 years). The full sample was aged 9-15 in 1997*

15 This sub-group is tested separately to try to strengthen the evidence that the programme’s intended effects are not being achieved as a result of increased efforts by male partners to control transfer resources.